Most ERP failures aren’t caused by bad software. They’re caused by decisions made before a single screen of the new system ever gets configured. Gartner predicts that by 2027, more than 70% of newly implemented ERP projects will not fully achieve their original business goals. It also estimates that up to 25% of these projects will fail completely. 

That’s not a vendor problem. It’s a planning problem, and it’s exactly what a Microsoft Dynamics 365 Business Central consultant is hired to prevent. 

What Is Dynamics 365 Business Central Consulting? 

Dynamics 365 Business Central consulting is the advisory work that helps organizations evaluate ERP readiness, assess business processes, define requirements, and build an implementation roadmap before deploying Microsoft Dynamics 365 Business Central. It answers the “what” and “why” before implementation partners handle the “how.” 

A common misconception is that Dynamics 365 consulting and Dynamics 365 implementation are the same service delivered by the same people at the same time. In practice, they’re different disciplines that require different mindsets. 

What Does a Business Central Consultant Do Before ERP Implementation? 

Prior to implementation, a consultant analyzes existing business processes, determines gaps between the processes and the capabilities of the platform, establishes data and integration needs, and creates a realistic roadmap with concrete deliverables. The idea is to eliminate guess work until budgets and timelines are concrete. . 

Understanding the Strategic Role of a Business Central Consultant 

Consultants are more in line with business analyst with extensive knowledge of the Microsoft platform than a traditional IT vendor. They sit between your business stakeholders and the technical build team, translating operational reality into system requirements. 

Why does this matter? Because most ERP problems are not technical. Microsoft Dynamics 365 ERP has applications like Business Central for small and medium businesses, Dynamics 365 Finance for financial management, and Dynamics 365 Supply Chain Management for manufacturing and supply chain operations. These solutions are mature and well-documented. Failures in implementation are usually more organizational than technological.  

Addressing Organizational Risks Before ERP Implementation 

Most projects fail for the same reasons. No one owns the process. Nobody wrote it down. The timeline was never realistic. Executives never agreed on what “done” means. 

Forrester’s ERP research backs this up. The real problem isn’t technology. It’s change management and whether the organization is ready. 

A good consultant surfaces these issues early, when they’re a conversation, rather than late, when they’re a change order. 

ERP Consultant vs. Implementation Partner vs. Internal IT Team 

These three roles get confused constantly, and the confusion is expensive. Each has a different focus, and none of them fully replaces the others. 

How Consultants Align Business Goals with Technology 

A Dynamics 365 Business Central consultant’s job isn’t to recommend features, it’s to connect a business outcome (faster financial close, better inventory visibility, fewer manual reconciliations) to a specific configuration decision. Without that connection, implementation teams end up building what was requested instead of what was needed. 

This alignment work typically involves structured stakeholder interviews across finance, operations, sales, and IT, followed by workshops where competing priorities get reconciled before they become mid-project conflicts. 

Why Early Engagement with a Business Central Consultant Improves ERP Success 

Early involvement allows stakeholders to agree on priorities, cleanup data, and establish a timeline for complexities that is based on real data not a vendor’s sales quote.    

• Preventing Scope Creep 

Scope creep rarely happens all at once. It happens one “small addition” at a time, usually because requirements weren’t fully documented at the start. A consultant’s discovery process forces those decisions upfront, when they’re cheap to make, instead of mid-build, when they trigger change orders and timeline slippage. 

• Identifying Business Process Gaps 

Every organization has processes that exist because “that’s how we’ve always done it,” not because they’re efficient. A consultant’s process mapping exercise typically surfaces workarounds, duplicate data entry, and manual approval chains that nobody had flagged as a problem. 

• Creating a Practical ERP Implementation Roadmap 

A roadmap built after proper discovery accounts for dependencies: data migration can’t finish before source systems are cleaned, integrations can’t be tested before APIs are confirmed, and user training can’t start before configuration is stable.  

• Improving Budget and Timeline Predictability 

Most ERP budget overruns trace back to underestimated complexity discovered mid-project. A thorough readiness assessment surfaces that complexity, legacy data problems, undocumented customizations, unclear integration requirements, before a number gets attached to the project. 

• Building Executive and Stakeholder Alignment 

ERP projects fail politically as often as they fail technically. When finance, operations, and IT have different definitions of success, the project has no way to satisfy everyone. A consultant-led discovery process gets those definitions reconciled and documented before implementation, so disagreements get resolved in a workshop instead of a go-live retrospective. 

7 Critical Areas a Business Central Consultant Evaluates Before Implementation 

Before recommending an implementation approach, an experienced consultant systematically evaluates seven areas: business processes, legacy systems, data quality, integrations, platform fit, security and compliance, and change readiness.  

1. Business Process Assessment

This is the foundation of everything else. The consultant documents how work actually happens today, order-to-cash, procure-to-pay, financial close, inventory management and identifies which processes should be standardized, which need custom configuration, and which are candidates for elimination altogether. 

2. Legacy ERP & System Evaluation

Understanding what you’re moving away from matters as much as understanding what you’re moving to. This includes reviewing existing customizations, undocumented workarounds, and any dependencies other systems have on the legacy platform. Beyond Key’s case study on a manufacturer’s migration from Dynamics GP to Dynamics 365 Business Central is a real example of what this evaluation looks like in practice, legacy customizations and reporting dependencies had to be catalogued before the migration path could be finalized. 

3. Data Quality and Migration Readiness

Bad data doesn’t get better by moving it to a new system, it just becomes bad data in a more expensive place. IBM’s Institute for Business Value has found that 43% of chief operations officers now identify data quality as their most significant data priority, and more than a quarter of organizations estimate annual losses over $5 million tied to poor data quality. 

4. ERP Integration Requirements

Dynamics 365 is not often a standalone solution. It usually must integrate with CRM software, eCommerce platforms, payroll, warehouse management or industry-specific applications. It is useful to map these points early in the process so as to prevent costly rework after go-live. 

5. Choosing Between Business Central and Finance & Operations

This choice influences nearly everything downstream, from cost to time, complexity and scalability of the long term. A consultant will assess the size of the company, a number of transactions, the extent of worldwide operations, and the complexity of the industry, to determine which is the most appropriate. 

6. Security, Compliance & Governance Planning

Before configuration, it is essential to understand the role-based access requirements, data residency requirements, and industry-specific compliance requirements. This is crucial for companies within the regulated sector such as healthcare, financial services, and manufacturing. 

7. User Adoption & Change Management Strategy

The best-configured ERP system still fails if the people using it don’t trust it or don’t know how to use it. A consultant identifies training needs, change resistance, and communication gaps before go-live, when they’re far easier to address.

8. AI Enablement & Copilot Readiness Assessment

As AI becomes more deeply embedded in Dynamics 365, consultants are looking at how Microsoft Copilot can add value across business functions. They assess data readiness, governance, security, licensing, and user adoption to ensure that AI capabilities are implemented effectively and aligned with business goals. 

The 5-Stage ERP Pre-Implementation Framework Used by Experienced Business Central Consultants 

The approach of experienced ERP consultants usually involve the following 5 steps prior to implementation: Discovery Workshops, Business Process Mapping, solution Fit-Gap Analysis, Project Planning, Executive Sign-Off.       

Stage 1: Discovery Workshop Structured session with stakeholders from different departments to gain a clearer understanding of their pain points, business goals and success metrics for the ERP project. 

Stage 2: Business Process Mapping Documentation of existing workflows in finance, operations, sales and supply chain, identifying inefficiencies and manual workflows. 

Stage 3: Solution Fit-Gap Analysis A structured comparison of documented business requirements and out-of-the-box Dynamics 365, highlighting the need for configuration, customization, or process change. 

Stage 4: ERP Project Planning & Implementation Roadmap A roadmap that outlines a phased approach to the project, including milestones, resources needed and dependencies as well as a realistic budget based on the complexity found in previous stages. 

Stage 5: Executive Sign-Off & Implementation Readiness Formal sign-off and approval from leadership to confirm that the scope, budget, timeline and success metrics are agreed to prior to finalising implementation contracts.    

Real-World ERP Implementation Scenarios: The Cost of Planning vs. Guesswork 

Scenario 1: Distribution Company That Skipped a Readiness Assessment 

Take for example a medium sized distribution company that implemented ERP without any sort of readiness study. There had not been any reconciliation of inventory data between the three different warehouse systems. After migrating, the implementation team identified thousands of SKUs that were duplicated and inconsistent unit-of-measure conventions. 

The outcome was a four-month project delay during data cleaning, which was a far more costly process than pre-implementation data cleaning, which would have been required by an audit. The company also needed to re-run UAT following the data corrections, resulting in a go-live that was well behind schedule. 

Scenario 2: Manufacturer That Invested in Consultant-Led Discovery 

Imagine a manufacturing organization that hired a consultant to help them go through a discovery period in order to choose an implementation partner. The discovery workshops showed that the company’s bill-of-materials design was not easily conformed to commonly-used Dynamics 365 manufacturing setups. 

Because this was identified during the fit-gap analysis rather than mid-build, the team adjusted the configuration approach before implementation started. The project stayed within its original timeline, and the go-live required minimal post-launch rework. 

These two illustrative patterns repeat across industries: the cost of discovery is always smaller than the cost of discovering problems during implementation. For a documented example of this same principle applied to a real engagement, Beyond Key’s Dynamics GP to Business Central migration case study walks through how a manufacturing client’s legacy system evaluation shaped its migration approach. 

Hiring a Business Central Consultant vs. Going Directly to ERP Implementation 

Organizations that engage a Dynamics 365 consultant before implementation typically get clearer scope, better budget accuracy, and fewer post-launch surprises than those that move straight to implementation.  

Comparison Table 

Checklist: Is Your Organization Ready for ERP Implementation? 

Consider using this checklist to assess readiness prior to enlisting an implementation partner. If there are more than 2 or 3 products that are not checked, it might be worthwhile to invest in a pre-implementation consulting engagement. 

ERP Readiness Checklist 

• Business objectives clearly defined 
• Current business processes documented 
• Executive stakeholders aligned 
• ERP budget approved 
• Data cleaned and validated 
• Integration requirements identified 
• Internal project owner assigned 
• Change management strategy prepared 
• Implementation timeline established 

Why Businesses Choose Beyond Key as Their Business Central Consultant 

A Business-First ERP Consulting Approach 

Beyond Key starts every engagement by understanding the business problem before recommending a technology configuration. That means discovery workshops, process mapping, and fit-gap analysis come before any conversation about specific modules or customizations. 

End-to-End Dynamics 365 ERP Consulting Services 

From initial readiness assessment through implementation, data migration, and post-go-live support, Beyond Key’s Dynamics 365 ERP consulting services and broader Dynamics 365 consulting practice are structured to keep planning and execution connected rather than handed off between disconnected teams. 

Expertise Across the Microsoft Dynamics 365 Ecosystem 

Beyond Key works across Business Central, Finance & Operations, and Dynamics 365 Customer Engagement, along with the broader Microsoft stack including Power Platform and Azure. This breadth matters when integration requirements span multiple systems, which is the norm rather than the exception for most mid-market and enterprise organizations. 

Certifications, Compliance, and Track Record 

Beyond Key operates as a Microsoft Solutions Partner and holds ISO 27001:2022 certification for information security management, alongside SOC 2 Type II compliance, both confirmed in the company’s own certification announcement and its most recent regional expansion news release. The company has been operating since 2005, has grown to more than 375 technology specialists and has been recognized as a Great Place to Work. 

Conclusion 

ERP implementation problems are rarely a surprise to the people who look closely beforehand. Data issues, unclear requirements, and misaligned stakeholders show up in a discovery workshop just as easily as they show up in a failed go-live, the difference is timing, and Gartner’s own data suggests most organizations are running out of time before they’ve even started. A Dynamics 365 consultant is there to control that timing. 

If your team is weighing ERP implementation and wants a clearer picture of what readiness actually looks like, Beyond Key’s Dynamics 365 consulting team can walk through where your organization stands before you commit to a timeline or budget. 

Frequently Asked Questions:

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Many enterprise machine learning and artificial intelligence projects do not make it to production value because their data foundation is not solid enough to support them. Common blockers include fragile data pipelines, fragmented data silos, poor data quality, and limited governance. A Forward Deployed Engineer (FDE) helps address these issues by working inside the client environment to connect business goals with production-ready data infrastructure. 

McKinsey’s The State of AI in 2025 tells a similar story from a different angle. Roughly 88% of organizations now report regular AI use in at least one business function. Yet the majority are still stuck in experimentation or pilot mode, with only about a third reporting that they’ve genuinely scaled AI across the enterprise. Data quality, fragmented architecture, and rigid legacy workflows are named again and again as the reason pilots never graduate. 

On paper, this looks like a technology gap. In reality, it’s rarely about the model. Gartner’s research team predicts over 40% of agentic AI projects will be canceled by the end of 2027, citing escalating costs, unclear business value, and inadequate risk controls, not underperforming algorithms. 

Author Expertise Note: Written by Beyond Key’s data engineering and AI implementation team, this article draws on enterprise data modernization work across Microsoft Fabric, Databricks, Snowflake, Azure, Power BI, and cloud-scale analytics environments. The recommendations below reflect hands-on experience fixing production data pipelines, improving data quality controls, and preparing enterprise data platforms for AI and machine learning workloads. 

Who this is for: This article is intended for technology leaders, data engineering heads, CIOs, CTOs, analytics leaders, and AI program owners who need to modernize unreliable data pipelines before scaling machine learning, generative AI, or real-time analytics initiatives. 

What is FDE and How They Support Data & AI Initiatives? 

A Forward Deployed Engineer (FDE) is a hands-on technical expert who works inside a client’s environment to solve production data and software problems. In data and AI initiatives, an FDE diagnoses pipeline failures, improves data quality, modernizes architecture, and helps internal teams move machine learning or generative AI use cases from pilot to production. 

How FDEs Support Data & AI Initiatives:

A Forward Deployed Engineer is an embedded technical engineer who works directly in a customer’s environment to turn business requirements into production software, data, or AI systems. FDEs are designed to troubleshoot pipeline issues, improve data reliability, enable governance, and accelerate AI-ready infrastructure in enterprise data programs.  

• Real-time pipeline diagnostics: quickly find and fix bottlenecks, data leaks and execution failures in your existing data flows.  
• Architectural modernization: Move legacy warehouse to modern cloud Lakehouse for scalable machine learning workloads. 
• Data quality enforcement: Include automated validation rules, cataloging and lineage tracking in data ingestion pipelines. 
• AI-ready feature and vector data preparation: Prepare reusable data assets so that standard ML models, analytics systems, and generative AI applications can use consistent and reliable inputs. 
• Cross-functional technical alignment: Work with internal tech teams to translate high level business goals into operational data pipelines. 

Why Broken Data Pipelines Stall AI Projects & How FDEs Help Fix Them 

Artificial intelligence systems rely on current, governed and reliable data. Broken pipelines, schema drift, duplicate records, stale transformations, missing lineage, and delayed processing can lead to bad predictions, unreliable dashboards, and bad generative AI responses. FDEs address these problems by diagnosing root causes in the live environment, refactoring pipeline logic, adding testing and monitoring, and building DataOps practices that keep downstream AI workloads reliable. 

The IBM Institute for Business Value puts a dollar figure on the same problem. Its 2025 research on the cost of poor data quality found that 43% of COOs now name data quality as their top data priority, and over a quarter of organizations lose upwards of $5 million a year because of it, a pipeline and governance line item, exactly the layer an FDE is built to own. 

Beyond Key FDEs: Embedded Data Engineers for Microsoft Fabric, Databricks, Snowflake, and Enterprise AI Platforms 

Beyond Key does not offer typical advisory consultants who deliver slide decks and leave. With over 20+ years of end-to-end data consulting, BI expertise, and digital transformation excellence, Beyond Key provides Forward Deployed Engineers who function as an active, embedded extension of your core technology team. 

Beyond Key FDEs work across modern enterprise data platforms, including Microsoft Fabric, Databricks, Snowflake, Azure, Power BI, and Tableau. Their role is to apply platform-specific engineering practices to improve ingestion, transformation, governance, observability, and cost performance across the client’s data estate. 

Microsoft Fabric Certified Experts: Beyond Key is recognized among a select group of Microsoft partners globally for specialized Microsoft Fabric expertise. Our FDEs unify data engineering, real-time analytics, and data governance into single-tenant SaaS architectures. 

Databricks Certified Engineers: Expert in designing unified Delta Lake architectures, orchestrating automated Spark workflows, and implementing feature stores based on machine learning. 

Snowflake Certified Data Architects: Expert in multi-cluster warehouse optimization, zero-copy cloning, secure data sharing, and query performance optimization for cost efficiency. 

Beyond Key’s FDE model combines platform engineering depth with cross-industry delivery experience across manufacturing, healthcare, financial services, retail, and logistics. Each engagement should define measurable outcomes, evidence sources, and governance checkpoints so the work remains accountable and easy to validate. 

Common Data Quality Issues an FDE Can Help Solve 

The data quality problems vary from industry to industry, but the root causes are often the same. Data can be duplicated across multiple systems, in different formats and can change without warning. These problems can be a big roadblock when a business is trying to build AI applications. 

A Forward Deployed Engineer can work with the client’s existing teams to find these issues and fix them at the source. 

Manufacturing: Connecting Data From the Shop Floor 

A manufacturer can collect data from machines, ERP systems, quality platforms and maintenance applications. But the problem is, these systems don’t always play nice with the same data formats or refresh their data simultaneously. 

For example, a machine may record its production data using one equipment ID, but a different identifier is used for the same machine in the maintenance system. These inconsistencies can impact the quality of results when this data is integrated for an AI use case. 

An FDE can work with the data and engineering teams to map these sources, normalize key fields, find duplicate or missing records, and add automated checks to flag new issues. 

This results in a more reliable data basis for use cases such as predictive maintenance, production monitoring and quality prediction. 

Healthcare: Responding to Changes in Clinical Data 

Healthcare data may originate from EHR systems, labs, medical devices and other applications. A small change in the structure of incoming data can break a downstream pipeline. 

For example, a healthcare system may add a new field or change the format of an existing field without updating the data pipeline that relies on it. Organizations can implement automated checks to catch these changes early instead of discovering them when an analytics or AI workflow breaks. 

FDE can be used to enforce schema validation, pipeline testing, data quality rules and alerts for unexpected changes. 

This results in a more stable data environment for analytics and AI applications that rely on timely and consistent clinical data. 

Logistics: Creating a Single View of Shipment Information 

Logistics companies tend to handle the data from order management systems, warehouse systems, transportation systems, customer databases, and tracking systems. It is difficult to assemble all of this information when different systems use different formats or identifiers. 

For example, a single shipment that has a slight difference in customer or order information between two systems. If you don’t have good data validation and matching, the same shipment can show up as multiple records. 

An FDE can help link these data sources, establish common data definitions, clean duplicate records and put validation rules in place. 

Better-connected data gives businesses a stronger foundation for AI use cases such as shipment tracking, delivery prediction, customer service assistants, and operational analytics. 

Financial Services: Preparing Data Before Building AI 

Lenders typically have years of customer and transactional data that lives in legacy systems and newer cloud platforms. Bringing this data into a common environment does not mean it is AI-ready. 

For example, the same customer may be identified differently in different systems, or transaction records may have missing or inconsistent fields. These challenges can impact analytics and AI model accuracy. 

An FDE can assist teams in identifying these gaps, setting data quality rules, improving the exchange of data between systems, and automating the checking of unexpected or incomplete information. 

This gives teams a cleaner, more consistent data foundation for applications such as fraud detection, risk analysis, customer insights and other AI initiatives. 

Why You Need a Beyond Key FDE for Structuring Your Company Data 

Choosing a Beyond Key FDE means securing an elite technical partner who treats your business outcomes as their own metric of success. 

Traditional Staff Augmentation vs. Beyond Key FDE 

Key Success Indicators & USPs of a Beyond Key FDE: 

1. Direct Value Creation Over Billable Hours: Our FDEs measure success by operational metrics pipeline latency reduction, query cost savings, data reliability, and model deployment speed. 

2. Architectural Cost Optimization: Beyond Key FDEs do not just build pipelines; they optimize compute and storage configurations across Snowflake, Fabric, and Azure to significantly lower cloud running costs. 

3. Internal Knowledge Transfer: Beyond Key FDEs do not create reliance. They upskill your internal team, leaving behind clear documentation, clean codebases, and maintainable DataOps frameworks. 

How the Deployment of an On-Site Beyond Key FDE Can Help Fix Critical Data Gaps 

Measurable outcomes to track: Pipeline uptime, data freshness, schema-change failure rate, duplicate record rate, data quality test coverage, model deployment lead time, query cost, compute utilization, incident response time, stakeholder adoption of AI-ready datasets. 

When data challenges impede strategic AI goals, remote advisory often fails to deliver because of communication silos and a lack of contextual alignment. An On-Site Beyond Key FDE fills these operational gaps with active, localized integration into your day-to-day. 

Beyond Key’s Core Key Success Indicators:  

• Faster Time-to-Insight: Get from raw and unstructured data to cleaner analytics streams faster through reduced manual handoffs, improved pipeline automation, and standardized data quality checks.  
• Zero-Trust Data Governance: At the time of initial pipeline build, enforce native role-based access control (RBAC), row-level security, and audit logging.  
• Engineered System Reliability: Zero data downtime for mission-critical processing workflows. 

How an On-Site FDE Fills Critical Data Gaps:  

• Eliminating Contextual Friction: Get domain-specific data nuances off-site teams miss, sitting beside your data scientists, domain experts and IT leaders, on-site Beyond Key FDE removes contextual friction.  
• Real-time Root-Cause Analysis: For data pipeline failures or ETL process failures, an on-site FDE analyzes the failure point immediately and executes code fixes immediately without waiting for ticket queues.  
• Direct Stakeholder Alignment: The FDE translates business requirements directly into underlying data pipelines, ensuring your technical foundation is directly serving core revenue goals. 

Q&A Checklist: 15 Questions to Ask Before You Hire an FDE 

What technical skills does your FDE have for data and AI projects? 

A good answer covers data engineering, Python, cloud platforms, DataOps, APIs, AI architectures, LLM evaluation, and Power BI. 

How is an FDE different from a DevOps engineer? 

A good answer explains that FDEs work across data, application logic, AI, and business workflows, not just infrastructure and deployment. 

Can your FDE move an AI project from prototype to production? 

A good answer covers data pipelines, model evaluation, integrations, performance, and production guardrails. 

How quickly can an FDE start delivering value? 

A good answer explains how direct access to systems and teams removes onboarding and handoff delays. 

What access will the FDE need from our team? 

A good answer clearly outlines repository, cloud, communication, and domain-expert access requirements. 

How will the FDE work within our security environment? 

A good answer covers least-privilege access, existing cloud controls, permissions, and audit requirements. 

How will you protect our sensitive data? 

A good answer includes data masking, role-based access, lineage, monitoring, and secure data handling. 

Can an FDE fix broken data pipelines? 

A good answer covers root-cause analysis, pipeline fixes, testing, and ongoing monitoring. 

How does an FDE improve data quality for AI? 

A good answer includes validation, schema checks, anomaly detection, lineage, and automated testing. 

Can your FDE move GenAI applications into production? 

A good answer covers RAG, vector databases, LLM evaluation, performance optimization, and AI guardrails. 

How do you evaluate whether an AI solution is working? 

A good answer defines measurable metrics like accuracy, quality, latency, adoption, reliability and cost. 

Which data and AI platforms can your FDE work with? 

A good answer includes platforms such as Microsoft Fabric, Databricks, Snowflake, Azure, and Power BI. 

How will you measure the FDE’s impact? 

Metrics like data quality, pipeline uptime, time to deploy, cloud costs, and incident response would be a good answer. 

Will the FDE transfer knowledge to our internal team? 

Documentation, knowledge transfer, maintainable code and reusable DataOps practices is good answer. 

How is your FDE model different from traditional consulting? 

A good answer shows that FDEs work directly in the client environment and are measured by execution and business outcomes, not just recommendations. 

Partner With Us: Solve End-to-End Data Challenges and Scale AI with Beyond Key FDEs 

Organizations can use Forward Deployed Engineers to reduce technical debt, stabilize data pipelines, and improve AI readiness without waiting for lengthy hiring cycles or relying only on advisory reports. The model works best when business stakeholders, data teams, and platform owners align around measurable outcomes such as pipeline reliability, data quality, deployment speed, and cost efficiency. 

Enterprises leveraging Forward Deployed Engineers can shorten AI and machine learning deployment timelines when the engagement includes clear success metrics, access to production systems, stakeholder alignment, and measurable data quality improvements. 

Frequently Asked Questions

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The price of Dynamics 365 licenses varies roughly from $8 to $210 per user per month, depending on user type, tenant, device or deployment scale. Attach licensing can cut the cost of a second app by 70–85%, and once implementation, data migration, training, and support are factored in, most organizations spend two to five times the license price in Year 1. From Year 2 onward, costs typically settle to about 1.3x the license cost. 

If you’ve spent any time searching for straight answers on what Dynamics 365 actually costs, you’ve probably noticed a pattern: most pages give you a price list and stop there. That’s not a budget, it’s a starting bid. The license fee is real, but it’s usually only 20–30% of what an organization spends in the first year, once implementation, data migration, integrations, and training are added in. 

This guide walks through the whole picture: per-app pricing, how attach licensing actually works (with the math shown, not just claimed), what full implementation and total cost of ownership look like across company sizes, how Dynamics 365 stacks up against Salesforce and NetSuite on cost, and the licensing changes coming in 2026 that will affect your budget whether you’ve priced them in yet or not. 

What Is Dynamics 365 and How Does Its Pricing Model Work? 

Dynamics 365 isn’t a single product. It’s Microsoft’s family of cloud-based ERP and CRM applications, covering sales, customer service, finance, supply chain, field service, and project operations. Each application is licensed and priced separately, which is exactly why “how much does Dynamics 365 cost” doesn’t have a one-line answer. A five-person sales team and a 300-person manufacturing operation are buying two very different combinations of apps. 

Pricing follows a named-user, per-user-per-month model, billed monthly or annually. Rather than paying for a single “Dynamics 365” license, an organization licenses each application a user needs: Sales, Customer Service, Business Central, and so on, and pricing scales with both the app and the depth of functionality required (Professional versus Enterprise tiers, for instance). Layered on top of base app pricing is attach pricing, which rewards users who need more than one app with a steep discount on the second and subsequent apps. We’ll break that down with real numbers in the next section. 

For a broader look at what each application actually does, see our Dynamics 365 modules overview.

Dynamics 365 Pricing by Application (2026 Price List) 

Here’s where most pricing guides start and stop. We’re including it because it’s genuinely useful, just don’t treat it as your budget. 

Source: Microsoft  

How Attach Licensing Works (With Worked Examples) 

This is the part almost every competing guide skips, and it’s where real budget accuracy lives. 

Attach pricing means that once a user holds a “base” qualifying license. It is generally the highest-priced app they need; additional Dynamics 365 apps for that same user are priced at a steep discount, usually in the $20–$30 per user per month range, rather than full list price. 

Worked example: Sales + Customer Service: A user who needs both Sales Enterprise ($105/month) and Customer Service Enterprise ($105/month) would pay $210/month at standalone pricing. With attach pricing, the second app attaches at roughly $22/month, bringing the combined cost to about $127/month, a savings of nearly 40% for that user alone. 

The strategic lesson: sequence your purchase so that the most expensive app a user needs becomes their base license, and add everything else as attachments. Buying apps in the wrong order, cheapest first, forfeits most of this discount, since attach pricing only applies going up in tier, not down. 

Licensing Terms: Monthly, Annual, and Multi-Year 

Dynamics 365 is available on monthly, annual, and multi-year commitments, and the term you choose has real budget consequences beyond the sticker price. 

• Monthly billing: In this model, you can add or eliminate the seats according to your feasibility. Per-user rate is quite high but it is the best option for piloting a new tool or seasonal headcount.  
• Annual billing: Lower per-user rate, price locked for 12 months; reducing seat count generally has to wait until renewal. 
• Multi-year / Enterprise Agreement: Yearly billing prices can be easily negotiated. Cloud Solution Provider can help you with the pricing or direct Enterprise Agreement can do the same.  

Procurement teams should weigh workforce volatility against savings: an organization with unpredictable headcount often loses more to over-committed annual seats than it saves on the per-user discount. 

Beyond Licensing: True Total Cost of Ownership (TCO) 

License cost is the number everyone quotes and the number that matters least for budgeting. Here’s what shows up on the invoice over time. 

Implementation services costs by module 

Implementation scope and cost vary enormously by module and complexity. Business Central projects for smaller organizations tend to run $25,000–$80,000, while enterprise Finance and Supply Chain Management rollouts with heavy customization commonly land between $150,000 and $500,000+. 

Data migration, integration, and customization costs 

Migrating the current data to a new platform, integrating it to other platforms (r-commerce, banking, and more) and configuring the workflows: these add up to the project budget. Hence, the software license cost may exceed the estimated budget.  

Training and change management costs 

Organizations should estimate a budget for end-to-end training sessions and change management programs that can lead to faster adoption. This can add to better performance of Dynamics 365 post-launch.  

Ongoing support costs (Year 2+) 

After go-live, ongoing costs, support retainers, minor enhancements, and periodic optimization tend to stabilize significantly compared to Year 1. 

Hidden costs (Azure, Power BI, ISV apps, Copilot Credits) 

You might not know but there are several costs that add to the base subscription cost. Azure for custom integrations, ISV apps, Copilot, Power BI premium capacity are a few add-ons that are not included in the base subscription.  

Bottom line: expect Year 1 total cost of ownership at roughly 2–5x the annual license cost, settling to around 1.3x from Year 2 onward. For a deeper walkthrough of what a project timeline actually looks like, see our Dynamics 365 implementation timeline guide. 

Dynamics 365 Pricing by Company Size 

Small business (under 50 employees) 

Typically, Business Central plus a small number of Sales or Customer Service seats, with a lighter implementation scope and minimal customization. 

Mid-market (50–500 employees) 

Often a mix of Sales/Customer Service Enterprise plus Business Central or Finance, with moderate integration needs and multiple departments involved in rollout. 

Enterprise (500+ employees) 

End-to-end Finance and Supply Chain Management deployments, integrations, phased rollouts, heavy customizations etc. Across geogrophoes and business units.  

Dynamics 365 vs. Salesforce vs. NetSuite: Pricing Comparison 

At comparable tiers, Dynamics 365 is frequently less expensive than Salesforce, and attach pricing widens that gap further for organizations needing multiple apps per user. NetSuite’s tenant-based structure makes direct per-user comparison harder, since much of the cost sits in the base platform fee rather than a clean per-seat number. If you’re actively weighing a move from Salesforce, our Salesforce vs Dynamics 365 page covers the switching process in detail.

2026 Dynamics 365 Licensing Changes to Know 

Microsoft is removing previously seeded AI Builder credits from Power Platform and Dynamics 365 licenses starting in November 2026, shifting more AI-driven automation onto metered Copilot Credit billing. Organizations that built workflows around included AI Builder capacity should reassess usage now rather than after the change lands. Finance and Operations license validation is also getting stricter in 2026, meaning organizations with loosely tracked user assignments are more likely to face true-up costs at renewal. For AI-specific cost planning, see our Copilot for Dynamics 365: features and pricing breakdown. 

How Beyond Key Helps You Get Dynamics 365 Pricing Right 

Beyond Key is a Microsoft Solutions Partner confirm current designation, with more than 100 Dynamics 365 implementations completed across manufacturing, distribution, professional services, and retail clients. Rather than hourly estimates that leave budget open-ended, we work from a fixed-price-quote philosophy: a license mix review, module recommendation, and implementation scoping process that produces a proposal you can actually budget against. 

Our implementation approach 

Discovery → Design → Build/Configure → Data Migration → Training → Go-Live → Support — a phased methodology built to keep scope, timeline, and cost visible at every stage rather than surfacing surprises at the invoice. 

Customer success example

CGIAR Systems Organization implemented Dynamics 365 for Sales Module for donations, fundraising and volunteer management.

Download this case study to see how we helped them with license audit and increased ROI outcomes. See our Dynamics 365 case studies to know more about how we helped our customers with Dynamics 365 solutions.  

Our clientele: Fenix, CGIAR

Industries we serve 

• Manufacturing: Supply Chain Management-heavy configurations for inventory and production planning. 
• Distribution: Finance plus Supply Chain Management for multi-warehouse operations. 
• Professional services: Project Operations paired with Sales for engagement-based billing. 
• Retail: Customer Service and Sales Enterprise with commerce integrations. 
• Nonprofit: Business Central with grant and fund accounting configurations. 
• Financial services: Finance with heightened compliance and audit-trail requirements. 

Explore our full Dynamics 365 Services or our Business Central Services for module-specific detail. 

Frequently Asked Questions:

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Why Are Organizations Migrating VMware to the Cloud?

Quick answer: Organizations around the globe are increasingly migrating VMware to the cloud because of increased licensing costs by Broadcom, scalability issues, and the desire to move to the cloud for better data recovery and security concerns. 

VMware ran quietly in the background of most enterprise data centers for two decades. Then Broadcom bought VMware in 2023 and changed the rules. Perpetual licenses disappeared. Bundled subscriptions replaced à la carte pricing. Many IT leaders opened their renewal quote and found it two to five times higher than before. 

A widely referenced 2025 Forbes analysis summarizes the current market sentiment:

“Customers are scrambling for VMware alternatives or reluctantly accepting Broadcom’s new rules.”

Source: Forbes

That price shock started the conversation. But it isn’t the only reason teams are moving. Below are the driving factors behind the shift: 

• Shift in license prices: Higher costs and forced bundling pushed budget owners to look elsewhere. 
• Infrastructure modernization: Aging hardware refresh cycles are a natural trigger to rethink the whole stack. 
• Data center exit: Fewer companies want to own racks, cooling, and physical security anymore. 
• Disaster recovery: It is less expensive and more reliable in the cloud rather than VMware or secondary sites.  
• Operational cost optimization: With cloud, the finance department ensures that the expenses are tied to actual usage. 
• Security and compliance: Cloud supports automated patching and global compliance that are better than local data center capabilities.  
• AI and analytics readiness: Cloud supports adopting containers and managed services, which helps them embrace AI features and modernization.  

Before You Migrate: Ask These 7 Critical Questions 

Most VMware migration content jumps straight to tools. That’s a mistake. The right questions come first, and they shape every decision that follows. 

1. Are your applications cloud-ready? 

Some legacy apps assume local storage paths or hardware dongles. Find these before you plan a wave. 

2. What are your workload dependencies? 

An app rarely stands alone. Map what talks to what before you move anything. 

3. What downtime can the business tolerate? 

A finance system and an internal wiki have very different tolerance levels. 

4. Which workload should remain on-premise? 

Not everything needs to move. Some workloads are cheaper or safer where they are. 

5. Do you need application modernization? 

Some apps are worth refactoring during the move. Most are not, at least not yet. 

6. What compliance requirements apply? 

Data residency and industry regulations can rule out certain regions or services outright. 

7. Have you estimated migration costs? 

Include network, tooling, staff time, and parallel-running costs, not just cloud infrastructure. 

Answering these honestly, before vendor conversations start, keeps the project grounded in your actual environment instead of a generic playbook. 

Choosing the Right Migration Strategy 

Every workload fits one of six migration paths. Picking the wrong one is the single biggest cause of migration delays. 

VMware to Azure, AWS, or Google Cloud: Which Option Fits Your Business? 

The three major VMware-native cloud services look similar on paper. The differences show up in ecosystem fit. 

Azure VMware Solution 

Pros: It promotes deep integration with Entra ID, Microsoft 365, and existing Azure workloads. Suitable for businesses already using Microsoft tools.
Cons: Not so beneficial for organizations that are not Microsoft-centric.
Best for: Enterprises running Active Directory, M365, or Dynamics 365 alongside VMware. 

Google Cloud VMware Engine 

Pros: Powerful data analytics and AI tooling once workloads land in Google Cloud.
Cons: Not so big VMware-specific partner ecosystem compared to Azure and AWS.
Best for: Businesses who want to choose Google’s AI stack and BigQuery. 

VMware Cloud on AWS 

Pros: Mature service with strong global region coverage and comprehensive AWS service integration.
Cons: Pricing is complicated, and Microsoft workload integration is ineffective than Azure’s.
Best for: Organizations already leveraging workloads on AWS. 

VMware Migration Roadmap (Step-by-Step) 

A structured roadmap keeps a migration from turning into a series of fire drills. Each step feeds the next. Skipping discovery to save time, for example, usually shows up later as a missed dependency during cutover, which costs far more time to fix. 

Assess: Discover workloads, assess infrastructure, map dependencies, and evaluate cloud readiness. 

Decide: Select the migration approach, then plan networking and security requirements. 

Migrate: Run a pilot, execute migration waves, and validate workloads after cutover. 

Optimize: Tune performance, resolve issues, and optimize cloud costs for long-term efficiency. 

Microsoft recommends structured planning through the Cloud Adoption Framework paired with Azure VMware Solution guidance. This pairing gives teams a governance model alongside the technical migration path, rather than treating governance as an afterthought. 

VMware Migration Tools Comparison 

What are VMware Migration Best Practices? 

• Start with workload discovery, not tool selection 
• Categorize applications by business criticality 
• Build migration waves around dependency groups, not alphabetical order 
• Validate dependencies before, not during, cutover 
• Plan rollback procedures for every wave 
• Optimize network connectivity ahead of the first migration 
• Test disaster recovery in the new environment, don’t assume it 
• Automate repeatable steps where possible 
• Use pilot migrations to catch issues early and cheaply 
• Monitor post-migration performance for at least 30 days 
• Optimize cloud costs continuously, not just at go-live 
• Document governance so the next team doesn’t start from zero

What Are Common VMware Migration Challenges (and How to Overcome Them)?  

How Beyond Key Helps Simplify VMware Cloud Migration? 

Moving off VMware touches infrastructure, security, cost, and application teams at once. Few internal teams have bandwidth to run a full migration alongside their regular workload. Beyond Key supports each stage of that process, from the first readiness assessment through post-migration optimization: 

• Cloud readiness assessments that map your current VMware footprint against migration options 
• Azure expertise spanning Azure VMware Solution and native Azure services 
• Landing zone design built on Microsoft’s Cloud Adoption Framework 
• Migration planning across discovery, waves, and cutover 
• Infrastructure modernization for workloads that need more than a lift-and-shift 
• Managed cloud services after go-live 
• Security and governance reviews aligned to Zero Trust principles 
• Post-migration optimization for performance and reliability 
• Cost optimization and FinOps support to keep cloud spend predictable 

Beyond Key is a Microsoft Solutions Partner with 20+ years of experience. We are HIPAA compliant, SOC II Type and ISO Certified.  

Industries we serve: Healthcare, Manufacturing, eCommerce, Logistics, Finance & Banking, Education, Automotive and more. Here are the certifications our professionals hold: AZ-104 Microsoft Azure Administrator Associate, AZ-305 Microsoft Azure Solution Architect, AZ-400 Microsoft Certified: DevOps Engineer Expert, AWS Certified Cloud Practitioner, AWS Certified Solutions Architect – Associate and Terraform associate.  

One of our real-world case studies: 

Client name: SZUL, a renowned Manhattan-based online jeweler  

What they wanted: An attractive, heavily featured website with a database, high-end applications (both web and mobile), high storage, and computing capacity for fast performance and 24/7 availability.  

How did we help? Beyond Key helped SZUL set up AWS cloud computing services to increase website performance and handle extreme traffic during the peak season. Our cloud experts used load balancers, Amazon S3 Glacier, cloud-based Amazon S3 and a lot of features to improve the overall website’s performance. You can learn in detail how we helped SZUL perform well here.  

To learn more about our projects, you can download our case studies from here. 

Frequently Asked Questions: 

The post Migrate VMware to Cloud: Best Practices, Tools, and Common Challenges appeared first on Beyond Key.

Introduction 

Microsoft 365 gives your teams powerful tools to work from anywhere. But every new user, device, and app also opens a door. Microsoft Secure Score is the number that tells you how many of those doors are still unlocked. 

Identity attacks are not slowing down. According to Microsoft’s 2025 Digital Defense Report, identity-based attacks jumped 32% in just the first half of 2025, and password spray now accounts for 97% of them. 

At Beyond Key, an assessment does more than provide a score. It identifies security gaps across identities, devices, apps, data, and cloud workloads. It also highlights the most important issues to fix first. 

What is Microsoft Secure Score? 

Microsoft Secure Score is a built-in measurement inside the Microsoft Defender portal. It reviews your Microsoft 365 environment. It checks which recommended security controls are enabled. It then gives you a score based on Microsoft’s recommendations. 

Think of it less as a report card and more as a map. It shows you: 

• Where your security gaps sit today 
• Which fixes carry the most risk reduction 
• How your posture compares with similar organizations 
• How your score changes over time as you make improvements 

The score recalculates roughly every 24 hours, based on your current configuration, per Microsoft Entra’s Identity Secure Score guidance. That makes it a living picture, not a one-time snapshot. This is what separates measuring security from improving it. A score by itself changes nothing. Acting on the gaps behind it does. 

How Microsoft Secure Score Works: Understanding the Scoring Methodology 

Each recommended action inside Secure Score carries a point value. That value reflects how much risk the action removes, not just whether a box is checked. Enabling MFA for admin accounts greatly improves security. It has a bigger impact than changing minor app settings. At Beyond Key, we help clients understand which security actions matter most. This helps teams focus on high-impact improvements instead of chasing easy score increases. 

Secure Score groups these actions into categories that map to how attackers actually move: 

• Identity security: authentication, access, and privilege controls 
• Device security: endpoint compliance and protection 
• Data protection: classification, labeling, and loss prevention 
• Threat protection: detection and automated response 
• Compliance: policy and regulatory alignment 

Here is something most organizations get wrong: chasing a higher number is not the goal. Some recommendations will not fit every business. A hospital and a law firm do not share the same risk profile. The real goal is closing the gaps that matter most to your environment, not maxing out every category on the dashboard. 

What is a Good Microsoft Secure Score? 

There is no universal passing grade. A “good” score depends on your industry, your risk tolerance, and what data you handle. In our experience, most organizations start with low or average Secure Scores. Many have important security gaps. With the right remediation plan, they can significantly improve their security posture. 

A high score can still hide a real gap if it comes from low-impact settings. A lower score is not automatically dangerous if the missing actions carry little weight. The number is a starting point for a conversation, not the final verdict. This is also why Gartner’s cybersecurity guidance consistently frames security maturity as a continuous program, not a single benchmark to hit and forget. 

Architecture-Led Microsoft Security Framework for Improving Microsoft Secure Score 

Improving Secure Score takes more than working through a checklist. Organizations need an architecture that connects identity, devices, apps, data, and cloud protection into one working system.  

During Microsoft 365 security assessments, we regularly see MFA enabled for regular staff but missing for privileged accounts, the exact users attackers want most. Microsoft’s own threat research backs up why this matters so much: phishing-resistant multifactor authentication can block over 99% of identity-based attacks, yet many tenants still leave gaps in exactly the accounts that would benefit most. 

Here is how the six core layers fit together, and where we most often find gaps during a Microsoft Secure Score Assessment: 

• Microsoft Entra ID: Identity Protection Covers MFA, Conditional Access, Privileged Identity Management, and identity risk detection. Gaps here show up as weak authentication, unauthorized access, and accounts with more privilege than they need. 
• Microsoft Defender XDR: Threat Protection Covers endpoint protection, email security, identity threat detection, and automated response. Gaps here let malware, phishing, and advanced threats slip through. 
• Microsoft Intune: Device Management Covers device compliance, mobile device management, app protection, and BYOD controls. Gaps here mean unmanaged devices and unpatched endpoints. 
• Microsoft Sentinel: SIEM and Threat Intelligence Covers security analytics, threat hunting, investigation, and automated workflows. Gaps here mean poor visibility and slow response when something does go wrong. 
• Microsoft Purview: Data Protection and Compliance Covers data classification, sensitivity labels, DLP, and compliance management. Gaps here lead to data leakage and regulatory exposure. 
• Microsoft Defender for Cloud: Cloud Security Posture Management Covers cloud recommendations, vulnerability assessment, and hybrid workload protection. Gaps here mean cloud misconfiguration, which remains one of the most common ways breaches happen. 

The business case for getting this right is not abstract. IBM’s Cost of a Data Breach Report found that organizations with a mature Zero Trust approach saved an average of $1.76 million per breach compared with those without one. That single figure tends to get budget conversations moving faster than any dashboard screenshot. 

How to Perform a Microsoft Secure Score Assessment 

1. Review your current score. Inside the Microsoft Defender portal to see where you stand today. 
2. Identify high-risk gaps. Focus on actions tied to identity and privileged access first. 
3. Prioritize recommendations. By impact, not by how easy they are to implement. 
4. Implement security controls. In phases, starting with the highest-risk category. 
5. Monitor continuously. Since your score shifts as your environment, staff, and threats change. 

During one client engagement, we found legacy authentication enabled on a few mailboxes. The team disabled it to close the security gap. This improved the organization’s identity score within a few weeks. It also blocked a common attack method that cybercriminals still use. 

How Beyond Key Helps Improve Microsoft Secure Score 

Beyond Key runs Microsoft Secure Score Consulting engagements built around this same architecture-first approach. Our team delivers: 

• A full Microsoft Secure Score Assessment 
• A Microsoft 365 security posture review 
• Detailed security gap analysis 
• Architecture recommendations across identity, devices, data, and cloud 
• Hands-on Microsoft Security Services implementation 
• Continuous optimization through Microsoft Cloud Consulting Services and ongoing monitoring 

Beyond Key is a Microsoft Solutions Partner with ISO 27001:2022 certification. The team has experience in Microsoft security, cloud, and AI solutions. This includes Microsoft Copilot governance and security consulting. We do not just point at a dashboard. We help you fix what it shows, and we stay involved as your environment and your score evolve.  

If your Secure Score has been sitting untouched, that is worth a closer look. Contact our Microsoft security consulting team for a security assessment. We will help you understand your current security posture. 

Conclusion 

Microsoft Secure Score identifies where your Microsoft 365 environment is exposed. But a higher number alone does not make you secure. Strong security requires the right architecture, governance, and ongoing improvements. A Secure Score alone is not enough. Microsoft security experts help turn Secure Score into an action plan. This helps strengthen your security over time. 

Frequently Asked Questions:

The post Microsoft Secure Score Assessment: How to Identify and Fix Microsoft 365 Security Gaps appeared first on Beyond Key.

Microsoft Dynamics 365 is an AI-powered enterprise platform that brings end-to-end CRM and ERP capabilities together. It helps organizations streamline their sales, services, supply chain, marketing, and finance operations. Per your business requirements, you can select modules and categorize them into domains. So, you don’t have to pay for a one-size-fits-all solution.  

Quick answer: Microsoft Dynamics 365 overview in one line: it’s Microsoft’s modular, cloud-first suite of CRM and ERP applications, built on the Power Platform and Dataverse, used by businesses to run sales, service, finance, and supply chain operations from connected data. 

Dynamics 365 CRM vs. ERP; What’s the Difference? 

This is one of the most common points of confusion for anyone new to the platform, and the honest answer is that Dynamics 365 isn’t strictly one or the other; it’s both, divided into separate applications. 

CRM applications in the Dynamics 365 suite focus on customer-facing work: tracking leads, managing service cases, scheduling technicians, and running marketing campaigns. ERP applications focus on the back office: financial reporting, inventory, procurement, manufacturing, and payroll-adjacent HR processes. A company might run only the CRM side, only on the ERP side, or both together, depending on what problems it’s trying to solve. 

A company might run only the CRM side, only the ERP side, or both together, depending on what problems it’s trying to solve. 

For a deeper breakdown of how each individual application fits into a broader rollout, see our Dynamics 365 implementation guide or our overview of Dynamics 365 Customer Engagement (CE). 

Dynamics 365 CRM Applications  

The CRM side of Dynamics 365 is what most mid-sized businesses evaluate first, largely because it competes directly with Salesforce and HubSpot. Each app below can be licensed on its own or bundled together. 

Dynamics 365 Sales 

Dynamics 365 Sales is the pipeline and opportunity management application. It gives sales teams a structured view of leads, deals, forecasts, and relationships, with AI-assisted features that flag at-risk deals and suggest next steps based on email and meeting activity. Sales Enterprise adds forecasting, playbooks, and deeper customization compared to the entry-level Sales Professional tier. Teams already using Outlook and Teams tend to adopt it faster because activities sync directly into the CRM record without extra data entry. 

Dynamics 365 Customer Service 

Dynamics 365 Customer Service is the case-management and support application. It routes tickets, tracks SLAs, and gives agents a unified view of a customer’s history across channels, chat, email, phone, and self-service portals. Copilot-assisted case summarization and suggested responses have become a bigger differentiator in recent releases, cutting down average handle time for agents working high case volumes. 

Dynamics 365 Field Service 

Dynamics 365 Field Service manages on-site technicians: scheduling, dispatching, work orders, and inventory tracking for parts used in the field. It’s built for industries like HVAC, utilities, and equipment maintenance, where a technician’s calendar, van stock, and customer contract terms all need to line up before a truck rolls. Resource scheduling optimization can auto-assign jobs based on technician skill, location, and availability rather than manual dispatch boards. 

Dynamics 365 Customer Insights (Marketing) 

Dynamics 365 Customer Insights combines what used to be two separate products; Customer Insights (data) and Dynamics 365 Marketing into a single customer data and journey-orchestration app. It unifies customer profiles from multiple sources, builds segments, and triggers real-time marketing journeys across email, SMS, and other channels. For businesses trying to personalize outreach without stitching together a separate CDP, this is the module that closes that gap. 

• Read more: Dynamics 365 For Marketing – What It Is and How It Helps. 

Dynamics 365 ERP Applications  

The ERP side runs the parts of a business that customers never see directly, but that keep the business solvent. These modules are more complex to implement than the CRM apps and usually involve a longer rollout timeline. 

Finance 

Dynamics 365 Finance handles general ledger, accounts payable and receivable, budgeting, and financial reporting for mid-sized to large organizations, with built-in compliance and multi-entity, multi-currency support. 

Check out this: Microsoft Dynamics 365 Finance & Operations vs Business Central 

Supply Chain Management 

Dynamics 365 Supply Chain Management covers inventory, procurement, manufacturing, and warehouse operations, with planning tools designed to help businesses respond to demand shifts and supplier disruptions. 

Business Central (SMB-tier ERP) 

Business Central is the ERP application built specifically for small and mid-sized businesses that need core financial and operational management without the complexity or cost of the full Finance and Supply Chain Management apps. 

Human Resources 

Dynamics 365 Human Resources manages employee records, benefits administration, leave and absence tracking, and compensation planning, integrating with payroll systems rather than replacing them outright. 

How Dynamics 365 Apps Work Together (The Platform Layer) 

What separates Dynamics 365 from a pile of unrelated software is the platform underneath it. Every core app- Sales, Customer Service, Field Service, Customer Insights, and most of the ERP suite reads and writes to Dataverse, Microsoft’s shared business data platform. That means a service opened in Customer Service can reference the same customer record used in Sales, without a nightly sync job or a third-party integration tool holding it together. 

On top of Dataverse sits the Power Platform: Power BI for reporting, Power Automate for workflow automation, Power Apps for custom interfaces, and Copilot Studio for building AI agents. A Dynamics 365 application isn’t really a closed box, it’s a starting point that most businesses eventually extend with a Power Automate flow or a Power BI dashboard pulling straight from the same data. This is also where pairing Dynamics 365 with Power BI reporting tends to pay off, since finance and sales leaders get a single source of truth rather than exporting spreadsheets from separate systems. 

The Dynamics 365 release plan for 2026 release wave 1 announces the latest updates to customers as features are prepared for release.  

Source: Microsoft   

Microsoft Dynamics 365 Pricing & Licensing 

Dynamics 365 pricing is per-user, per-month, and it varies significantly by application. As a general guide for 2026: 

Two things matter more than the sticker price. First, Microsoft’s “attach” pricing model rewards multi-app adoption; once a user has a full-price base license, additional qualifying apps are typically far cheaper, which is why bundling Sales with Customer Service, for instance, often costs less per app than buying either alone. Second, the license fee is only one line item. Implementation, data migration, integrations, and training commonly cost several times the annual license total, particularly for ERP rollouts. 

Dynamics 365 vs. Salesforce (and Other CRMs) 

This comparison comes up in nearly every CRM evaluation, and there isn’t a universal winner; the right platform depends on what a company already uses and how complex its processes need to be. 

Who Uses Microsoft Dynamics 365? (Industry & Company-Size Fit) 

Dynamics 365 is used across a wide range of industries, but a few patterns show up consistently: 

• Manufacturing and distribution: Supply Chain Management and Finance for production planning, inventory accuracy, and multi-entity reporting. 
• Field-service-heavy industries (utilities, equipment maintenance, facilities): Field Service for scheduling and work-order management. 
• Professional and financial services: Sales and Customer Service for pipeline visibility and client relationship management.  
• Small and mid-sized businesses: Business Central as an all-in-one ERP without enterprise-level complexity or cost. 
• Enterprise organizations: Full-suite deployments combining CRM and ERP apps with custom Power Platform extensions. 
• Nonprofits: CRM apps adapted for donor and grant management; see ERP for Nonprofits: A Comprehensive Overview, Donor Cultivation for Nonprofits. 

How to Choose the Right Dynamics 365 Modules 

Most businesses over-scope their first Dynamics 365 purchase. A more reliable approach is to work backward from the specific problem being solved: 

1. Identify the pain point first: find out what the challenge is that your business faces. From inventory accuracy to manual financial close, and slow resolution of issues, what are your pain points? 
2. Find out your current tech stack: using rigorous Microsoft 365 strengthens the case for Dynamics 365 over a non-Microsoft alternative. 
3. Check attach pricing before bundling: if a second or third app is needed within the first year, factor attach discounts into the total cost comparison rather than pricing each app in isolation. 
4. Separate “need now” from “need eventually”: Dataverse means additional apps can be layered in later without re-platforming, so there’s rarely a reason to buy every module on day one. 
5. Loop in an implementation partner early: for anything beyond a single CRM app, a certified partner can flag licensing traps and integration gaps before they become expensive to fix. 

AI, Copilot, and intelligent capabilities  

Copilot in Dynamics 365 apps helps users connect data with Teams and MS Outlook. As it offers no-code tools, even people with non-tech background can automate workflows, build apps and enhance productivity. D365 platforms are backed by built-in AI, advanced analytics, and the Internet of Things, which ensures your organization is agile and future-ready. Using Copilot Studio, you can create custom agents and make faster decisions for every department.   

Related Reading: 

• Microsoft Dynamics Copilot – The First AI-Powered CRM System 

• How is Copilot in Business Central Transforming ERP with AI? 

• AI Agents in Business Central: ERP Automation and Insights. 

Final Takeaway   

Microsoft Dynamics 365 isn’t one product, it’s a modular suite of CRM and ERP applications built on a shared data platform, which is exactly what makes it flexible enough for a 40-person business and a multinational enterprise alike.  

The apps that matter most depend entirely on where the operational pain actually is: sales visibility, service response time, field logistics, or financial reporting. Pricing and licensing are the parts most businesses get wrong, so it’s worth confirming current rates and attaching eligibility before committing to a rollout. 

Beyond Key has been helping global customers with implementing, integrating, and customizing the Microsoft Dynamics 365 platform with minimal disruption. We have been doing this since 2 decades.  

We developed custom-built CRM tailored to specific mission-driven interests of CGIAR. Using the CRM the non-profit was able to execute better levels of service, reduce internal costs, make smarter decisions, and increase the level of resources going directly to beneficiaries. You can download the case study here.  

Frequently Asked Questions 

The post What Is Microsoft Dynamics 365? A Complete Guide to Modules, Pricing, and Use Cases appeared first on Beyond Key.

Introduction  

Most organizations’ attack surfaces have widened with cloud adoption. Within minutes, all sensitive information can be exposed because of one misconfiguration. Many penetration testing firms, however, are still using methods that are developed for traditional on-premise networks. To close the divide, you must choose a cloud provider who has a proven track record of cloud expertise. This guide tells you exactly what to look for.  

What Is a Cloud Penetration Testing Company?  

A cloud penetration testing firm will attempt to hack into your cloud system using real-world attacks, before malicious hackers attempt to do so, with your permission. Typically, this involves discovering weak identity and access management settings, unsecured storage, misconfigured cloud services, and misaligned security solutions between your organization’s internal security and the security solutions you are provided by the cloud platform.  

This work is very different from traditional network penetration testing, which generally focuses on physical servers, firewalls, and internal office infrastructure. The model on which the cloud operates is quite different. Identity and access management, shared infrastructure, and automated services are big parts of what they do, so they need a different testing approach and skill set.  

A competent provider should have practical experience with the leading cloud platforms, including Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) as a lot of organizations use more than one.  

Why the Right Choice Matters  

Choosing the wrong provider isn’t just a waste of budget. It can have meaningful security gaps in place and at the same time, it can create a false sense of assurance within the organization.   

A well-qualified partner benefits your organization by:  

• Discovering weaknesses before the hackers do 
• Minimizing the risk and impact of an expensive data breach 
• More efficient support of compliance requirements 
• Building trust with customers, partners and regulators 
• Reducing remediation costs by identifying problems early 
• Increasing overall confidence in your cloud security posture  

Traditional Penetration Testing vs. Cloud Penetration Testing 

7 Key Factors to Consider When Choosing a Cloud Penetration Testing Company  

1. Cloud-First Knowledge 

Inquire with the provider directly about the amount of hands-on experience they have with AWS, Azure, and Google Cloud. Each platform may offer different services, settings, and default configuration, so may have strengths on one platform and weaknesses on another. Cloud providers operate based on the Shared Responsibility Model: the provider is responsible for the underlying infrastructure; your organization is responsible for the configuration and utilization of the services.  

2. Check Industry Certifications 

One of the simplest ways to assure a minimum level of skill is through certifications. Seek out certifications like CREST, OSCP, OSCE, CISSP, CEH, and cloud-based certifications, like AWS Security Specialty. While these do not necessarily indicate good work, they demonstrate that the provider has been assessed against a known standard and maintains an up-to-date approach to a changing subject area. Certifications are just one of several considerations and should not be the determining factor when selecting a provider. 

3. Take Their Testing Methodology into Account  

Inquire about their methodology and the frameworks they follow like OWASP Testing Guide, NIST guidelines, PTES, or MITRE ATT&CK. These exist for the sake of consistency in testing and thoroughness. Also, it would be helpful to know the percentage of manual versus automated work. While automated tools are helpful for general coverage, an experienced tester is likely to uncover real problems that automated tools will fail to detect. 

4. Consider Experience in the Field 

A provider who has actually worked in your field, such as healthcare, finance, SaaS, manufacturing, or even government, brings one thing automated tools can’t: context. They know what kinds of risks are likely to appear in your particular environment, as well as how the rules affect you and what the limitations are. Often this familiarity comes through in the quality of the findings because the team already knows what to look for and why it is important. 

5. Reporting and Remediation Assistance

A good report isn’t just a list of problems. It should contain an executive summary geared to leaders, unambiguous risk ratings, and the detail that your engineering team can react to. For each vulnerability, there should be evidence of their possible use, rather than just an assertion. Equally significant, the report ought to offer your team the fix step-by-step so remediation is not a guessing game. 

6. Understand Compliance Capabilities 

Be sure that the testing conforms to a standard such as ISO 27001, SOC 2, HIPAA, PCI DSS, or GDPR, not that it is “supposed to be” compliant. If the assessment matches what the auditors would be looking for, it can be very helpful to ease the burden during formal assessment and minimize back-and-forth communication afterwards. 

7. Find Out More About Their Reputation, Case Studies, and Client Reviews 

It’s a provider’s track record that tells you a lot. Search for genuine client feedback, case studies, industry acknowledgements, and indications of ongoing client associations. A provider with a strong confidence in their work is likely to be able to provide references or track record. If you don’t see any signs of commitment on this side or if they give you any vague answers when you ask them to provide evidence, take note. 

Top 9 Cloud Penetration Testing Companies 

9. Redscan 

Redscan is best known as a managed detection and response provider, with penetration testing offered as an add-on, rather than as a core specialty. They have cloud testing capabilities, but the company’s focus and resources are more suited to continuous monitoring and threat detection. This can mean less specialized depth for organizations that specifically prioritize deep, cloud-native penetration testing, compared to firms built around offensive security alone. 

8. TrustedSec

TrustedSec are well known in the offensive security consulting space, providing a full range of services from red teaming, incident response through to security program development. They have well-known consultants in the industry and technically the firm is seen as rigorous. That being said, cloud-specific testing is only a part of a much bigger portfolio, so clients looking for just cloud expertise may find it not the primary focus of the engagement. 

7. Praetorian

Praetorian is primarily working with large enterprises and is known for advanced adversarial simulation and offensive security research. The company has a good technical reputation and has made significant contributions to the security research community . However, their engagement model and pricing tends to be geared towards larger organizations, making them less accessible for small and mid-size businesses. 

6. Coalfire 

Compliance-driven security assessments are a popular choice for Coalfire, especially for companies in regulated industries such as finance and health care. They are great at testing against audit and certification requirements and are a go-to for compliance-first engagements. The extent of manual, cloud specific testing will vary from engagement to engagement based on scope and the assigned assessor.

5. Rhino Security Labs 

Through public research, Rhino Security Labs has built a strong technical reputation around AWS and cloud-specific research and has contributed to the security community. The testers are known for finding truly novel cloud misconfigurations and attack paths. However, some clients have noted that reporting depth and post-engagement remediation support may be inconsistent across projects.

4. Astra Security 

Astra Security has positioned itself as a budget-friendly option for startups and mid-sized companies with a mix of automated scanning and manual testing at a lower price point. That makes it attractive to teams with smaller budgets or security programs that are earlier in their maturity.  The downside is that engagements may rely more on automated tooling than fully manual, enterprise-grade testing approaches.

3. Cobalt.io 

Cobalt.io is a pentest-as-a-service platform that utilizes a distributed network of freelance testers, assigned per engagement. This method gives companies that conduct frequent, smaller-scope tests faster turnarounds and scheduling flexibility. The tradeoff is that continuity can suffer, as each time a different tester may be assigned, making it more difficult to achieve deep, ongoing familiarity with a client’s environment. 

2. Beyond Key

Beyond Key doesn’t have a generic, one-size-fits-all process for cloud security but a deliberate hands-on approach with platform expertise in AWS, Azure and Google Cloud. The team holds industry certifications such as OSCP, CEH, and CISSP, as well as cloud-specific credentials like AWS Security Specialty, giving clients a verified skill baseline behind every engagement. Testing is done using established frameworks such as OWASP, NIST, and MITRE ATT&CK, and is more reliant on manual testing than an automated scan to do the work. The firm has also acquired real-world cross-industry experience in healthcare, finance and SaaS, as well as practical experience with compliance standards like SOC 2, ISO 27001, HIPAA and PCI DSS. 

Main features: 

• Framework-driven manual-first testing 
• Cloud Security Team – Specialized and Certified 
• Actionable reports with clear steps for remediation 
• Retesting standard included 
• Robust compliance alignment (SOC 2, ISO 27001, HIPAA, PCI DSS) 
• Team’s continuous support throughout engagements 

1. Fox Bishop

Bishop Fox is consistently ranked among the world’s top offensive security firms, attracting the best security talent and performing deep, manual, and rigorous engagements. Their research team has a solid public record of vulnerability discoveries and industry recognition. That kind of depth typically comes at a premium price and requires longer timelines to engage, which could be a consideration for smaller organizations or teams that require a quicker turnaround. 

Final Checklist for Choosing the Right Cloud Penetration Testing Company  

Before signing a contract, confirm that the provider offers:  

• Proven cloud platform expertise 
• Certified, experienced security professionals 
• A combination of manual and automated testing 
• Relevant industry experience 
• Strong compliance knowledge 
• Detailed, actionable reporting 
• Remediation support 
• Verifiable, positive client references 
• Transparent, clear pricing 
• Retesting included in the engagement  

Conclusion  

Don’t base your decision on price when choosing a cloud penetration testing company. That is, balancing expertise, methodology, and a real concern for long-term security outcomes. Use the checklist and questions in this guide to objectively evaluate providers and weed out vendors who can’t clearly and confidently answer them.  

Security protecting cloud resources isn’t a project; it’s a duty. The perfect testing partner is the extension of your team, that brings added value beyond the engagement. 

Frequently Asked Questions

The post 10 Best Cloud Penetration Testing Companies to Consider in 2026 appeared first on Beyond Key.

What CEOs, CFOs, and CIOs need to know before committing capital to a data and AI platform.

Quick Answer 

Databricks and Azure Synapse Analytics solve different problems. Databricks is an open, multi-cloud Lakehouse built for AI, machine learning, and complex data engineering at scale. Azure Synapse Analytics is Microsoft’s SQL-first data warehousing service, tightly integrated with Power BI, but Microsoft has stopped meaningful new investment in Synapse and is directing customers toward Microsoft Fabric, its unified successor platform. The right choice in 2026 depends less on “which is better” and more on three questions: how AI-dependent is your roadmap, how committed are you to the Microsoft stack, and how much platform risk can your board tolerate.

Executive Summary 

Every data platform decision is ultimately a capital allocation decision. The technical differences between Databricks and Azure Synapse Analytics matter to your engineering teams; the strategic and financial differences are what matter in the boardroom.

This brief distills that decision into three dimensions that executives consistently underweight in vendor-led comparisons:

1. Microsoft has confirmed that new feature investment is concentrated in Microsoft Fabric, not Synapse. Choosing Synapse today is choosing a platform Microsoft is actively migrating its own customers away from.
2. Boards are no longer asking “can we build a dashboard?”; they are asking “can we deploy AI agents safely on governed data?” This single question now decides more platform votes than price or familiarity.

The short version: if your competitive advantage increasingly depends on AI, machine learning, and the ability to operate across multiple clouds, Databricks is the platform built for that future. If your needs are SQL-centric reporting tightly bound to the Microsoft ecosystem and you are prepared to plan an eventual move to Microsoft Fabric, Synapse remains workable in the near term, but it is no longer where new strategic investment should go.

What Are Databricks and Azure Synapse Analytics? 

Databricks: The Open Data Intelligence Platform 

What is Databricks? Databricks is a unified, cloud-agnostic platform built on Apache Spark, organized around the Lakehouse architecture, a design that combines the low-cost, flexible storage of a data lake with the governance and performance guarantees of a data warehouse. Rather than maintaining separate systems for data engineering, business intelligence, data science, and machine learning, Databricks unifies all four on one governed copy of data.

The platform runs natively on AWS, Microsoft Azure, and Google Cloud, so it is not tied to any single hyperscaler’s roadmap. Data is stored in Delta Lake, an open table format, inside the customer’s own cloud account, not inside Databricks-controlled infrastructure. For executives, this single fact has outsized importance: it preserves negotiating leverage and reduces switching costs, because your data remains in an open, portable format regardless of which compute engine you choose to run on top of it.

Azure Synapse Analytics: Microsoft’s Integrated Data Warehouse 

Azure Synapse Analytics is Microsoft’s integrated analytics service, combining enterprise data warehousing, big data processing, and data integration pipelines inside a single workspace called Synapse Studio. It was built to bring together SQL-based data warehousing (via Dedicated and Serverless SQL Pools) and Apache Spark-based big data processing under one roof, with tight native integration into Power BI, Azure Data Lake Storage, and Azure Machine Learning.

Synapse has historically been the natural choice for organizations with SQL-trained teams who needed enterprise-grade data warehousing without leaving the Microsoft ecosystem. That positioning, however, has shifted a point we address directly in Section 3, because it changes the calculus for any new investment decision made in 2026.

Note: Microsoft’s own modernization messaging is unambiguous: Fabric is positioned as the successor platform, consolidating Synapse, Power BI, Azure Data Factory, and Azure Data Lake into a single SaaS environment built on a shared storage layer called OneLake.

Side-by-Side Comparison: Architecture, Cost, and Capability 

The table below summarizes the dimensions that matter most to executive decision-makers. It is designed to be the one table your board needs.

Sources: Nucleus Research

Core Purpose

The purpose of Azure Synapse is to consolidate enterprise data warehousing and big data analytics into a single service. It is ideal for reporting, business intelligence, and structured data-related processes and tasks.

Databricks: Built around Apache Spark, Databricks is a unified data platform focused on data engineering, data science, and machine learning, suitable for large-scale processing and real-time analytics.

AI and Machine Learning Readiness

By 2026, the question boards that ask data leaders have fundamentally changed. It is no longer “can we report on our data”, it is “can we put AI agents into production safely on governed data, and how fast.” This is the dimension where the two platforms diverge most sharply.

Databricks’ Native AI Stack

• MLflow manages the full machine learning lifecycle: experiment tracking, model versioning, lineage to training data, and controlled promotion to production.
• Mosaic AI covers data preparation, training, serving, and monitoring as one connected workflow, with native support for PyTorch, TensorFlow, and Ray.
• Unity Catalog provides a single governance layer across all data assets, with automatic metadata collection and lineage tracking, a foundational requirement for deploying AI agents safely at enterprise scale.
• Foundation Model APIs and a dedicated Feature Store allow teams to build and reuse AI capabilities across departments rather than rebuilding them per project.

Synapse’s Approach

Azure Synapse connects out to Azure Machine Learning for model training and deployment. This works, but it requires wiring together separate services and moving data between them, an architecture pattern that adds integration overhead precisely where speed-to-production matters most for AI initiatives.

Collaboration

Azure Synapse: It offers limited collaboration capabilities compared to Databricks.

Databricks: Offers collaborative notebooks that support Python, R, Scala, and SQL, with version control and real-time co-authoring for teams.

Cost Considerations 

Azure Synapse offers more predictable pricing with its provisioned compute resources, which is advantageous for organizations with consistent workloads.

Databricks, on the other hand, charges based on compute usage, which can be cost-effective for organizations with fluctuating or high-intensity workloads, particularly when leveraging its real-time processing capabilities.

Use Cases  

Azure Synapse: Dashboard creation and reports, running serverless queries on raw files inside the Data Lake, consolidating structured data from multiple business systems into a centralized data warehouse.

Databricks: Data engineering and ETL, provides automated ML pipelines (AutoML) to train predictive models, process streaming data (e.g., IoT devices, financial transactions, log files) in real-time using Structured Streaming, etc.

You can also read our guide: Databricks vs. Snowflake or Databricks vs. MS Fabric

Decision Framework: Which Platform Fits Your Strategy? 

Choose Databricks If

• AI and machine learning are core to your competitive strategy over the next three to five years, not a side initiative.
• Your organization operates across more than one cloud provider, or wants to preserve that optionality.
• You need one governed platform for data engineering, analytics, and AI rather than several point tools with separate governance models.
• Your board is weighing platform decisions on a multi-year time horizon and wants documented, independently verified ROI.

Choose Azure Synapse If

• Your needs are primarily SQL-based reporting and business intelligence, tightly coupled to an existing Power BI deployment.
• You have well-performing existing Synapse workloads, and a migration is not yet operationally or financially justified.
• Your team’s skill set is deeply rooted in T-SQL and Microsoft tooling, and the lower learning curve is a genuine near-term productivity advantage.

Important caveat: if you select Synapse, do so with eyes open that Microsoft Fabric, not Synapse, is where the platform’s long-term roadmap is heading. Build your migration runway into the decision rather than treating Synapse as a permanent landing point.

The Hybrid Reality 

Many enterprises do not face a binary choice. A common and pragmatic pattern is to run Databricks for advanced analytics, data science, and ML, while keeping Synapse (or migrating to Fabric) for BI reporting teams already standardized on Power BI, using Azure Data Lake Storage Gen2 as the shared storage layer and Microsoft Purview for governance across both. This lets different teams work in the tool suited to their skill set while avoiding duplicated data copies.

Final Thoughts 

Platform decisions of this scale are rarely reversed cheaply once made. The data in this brief points to a clear pattern: organizations whose strategy depends on AI, machine learning, and cross-cloud flexibility have a well-documented, independently verified financial case for Databricks. Organizations with narrower, SQL-centric, Microsoft-only needs can still use Synapse productively today but should treat it as a bridge, with Microsoft Fabric as the more durable long-term Microsoft-ecosystem destination.

The question for your next leadership offsite is not “which platform has more features.” It is: “where do we want our data and AI capability to be in three years, and which platform’s trajectory matches that ambition?”

Want Assistance in Databricks or Synapse Analytics Consulting Services?

Book a Strategic Call with Beyond Key!

Beyond Key is a global IT consulting service provider that has been providing end-to-end services to global clients from last 20 years. You can contact us to deep dive into data platforms. From guidance to implementation and post-deployment process, we are here to assist you at every step.

Trusted by Industry Leaders: Breg, Taymor, GROW, and more. You can read the case studies here.

Frequently Asked Questions 

1. Is Databricks more expensive than Azure Synapse Analytics?

Not necessarily on a total cost of ownership basis. Synapse’s per-TB serverless pricing can appear cheaper for narrow reporting workloads.

2. Is Microsoft discontinuing Azure Synapse Analytics?

Microsoft has not announced a full discontinuation of Azure Synapse Analytics, and existing workloads remain supported. However, new feature investment has been redirected to Microsoft Fabric, several Synapse-specific components and reference architectures have been formally deprecated, and Microsoft’s own messaging positions Fabric as the long-term successor platform.

3. Can Databricks and Azure Synapse be used together?

Yes. Both platforms can share the same Azure Data Lake Storage Gen2 layer, allowing data engineers to transform data in Databricks and business analysts to query the processed output through Synapse SQL without duplicating data. This hybrid pattern is common during phased modernization.

4. Which platform is better for AI and machine learning workloads?

Databricks has a more mature, natively integrated AI stack, including MLflow, Mosaic AI, and Unity Catalog for governed lineage across all data assets. Synapse requires wiring together a separate Azure Machine Learning service, which adds integration overhead for AI-intensive workloads.

5. Should our organization migrate from Synapse to Microsoft Fabric or to Databricks?

It depends on your AI ambitions and cloud strategy. If your roadmap is Microsoft-centric and reporting-driven, Fabric is the more natural successor to Synapse. If your roadmap requires multi-cloud flexibility and deep AI/ML capability, Databricks is the stronger long-term foundation. Many enterprises evaluate both before committing capital.

The post Databricks vs. Azure Synapse Analytics: The 2026 Decision Guide appeared first on Beyond Key.

Cloud adoption is not slowing down. Neither are cloud bills. Companies usually underestimate the importance of cloud-cost optimization services. They don’t monitor the cloud usage, still pay for idle resources, and bulky infrastructures.  

In 2026, businesses across every industry are spending more on cloud infrastructure than ever before. But without managing cloud infrastructure costs, a large share of cloud spending will be unprofitable. It can drain budgets and hamper business growth.  

The good news? cloud spend management and best practices have matured. The tools are better. The strategies are proven. And companies that act now will hold a real competitive edge. 

Here is a quick look at how cloud cost optimization services work 

For example, an e-commerce organization has invested in 10 cloud servers and pay on a monthly basis. They didn’t monitor the cloud usage. After analysis, they found that out of 10 servers, 4 are unused, the databases are oversized, and traffic drops during the night hours. After they opted cloud cost optimization services, they have witnessed 35% reduced cost and decent annual savings.  

What service did they invest in? This e-commerce company has chosen Beyond Key to got reserved pricing plans, instances and auto-scaling implemented.  

Source: Cloudkeeper

Whether you are running workloads on AWS, Azure, Google Cloud, or a multi-cloud setup, this guide gives you ten actionable cloud cost optimization strategies you can implement today. 

1. Dive Deep into Cloud Spend Visibility  

You cannot cut what you cannot see. 

At the initial stage, make sure to have a clear plan about cloud spend optimization. Establish visibility and track spending by using an array of tools: Azure Cost Management, AWS Cost Explorer, Google Cloud Billing, etc., across departments, accounts, and locations. Tagging policies help the organization be accountable by labeling resources based on project, department, or team.  

2. Optimize Your Resources to Manage Workload Demands 

Most teams’ over-provision. They pick large instance types to be safe, and then those instances run at 10–20% utilization. Rightsizing means matching your compute, memory, and storage capacity to actual usage. Cloud providers offer built-in recommendation tools such as Google Cloud Recommender, Azure Advisor, AWS Compute Optimizer and more.  

You can analyze your workload history and leverage smaller, more efficient options with these tools. This single practice is among the highest-ROI cloud cost spend optimization solutions available.  

According to McKinsey Digital, the results of cloud optimization can be dramatic, allowing technology leaders to “quickly cut as much as 15 to 25% of the costs of their cloud programs while preserving their value-generating capabilities.” 

3. Use Reserved Instances and Savings Plans for Predictable Workloads

Reserved Instances are pricing models that can be used for cloud optimization in the cloud computing domain. It ensures predictable cost optimization. Organizations can run on mission-critical apps and cut 75% cost.  

4.Spot Instances for Workloads that are Flexible  

A few examples of workloads that work well in Spot Instances are CI/CD operations, High Performance Computing (HPC), distributed databases, containers, and microservices. Spot instances have become a powerful element in cloud cost optimization process.  

The trade-off is that these instances can be interrupted. For fault-tolerant workloads, that trade-off is very much worth it. 

5. Keep an Eye on Idle Resources 

Forgotten test environments. Elastic IPs with no instance attached. These are a few idle resources that are accumulated in active engineering environments. They are easy to miss and costly to ignore. By eliminating idle resources, you can identify inefficiencies. 

AWS Trusted Advisor, Azure Advisor, and open-source options like Infracost can flag these automatically. 

Source: Flexera  

6. Optimize Storage Tiers and Lifecycle Policies

Storage is often the most undermanaged part of a cloud environment. Not all data needs to live in high-performance, always-accessible storage. To match data value to cost-efficient storage classes, businesses should optimize storage tiers and focus on lifecycle policies.  

Storage tiers such as S3 Infrequent Access and Azure Cool Blob Storage can help businesses store infrequently used data.  

7.Monitor and Reduce Data Transfer Costs

Data transfer fees are a hidden tax on poorly designed cloud architectures. 

Moving data between regions, across availability zones, or out to the internet adds up. And unlike compute, these costs are not always visible until the bill arrives.  

Audit your data transfer patterns. Keep services that communicate with each other in the same region or availability zone, where possible. Use Content Delivery Networks (CDNs) for user-facing assets to reduce egress charges. This is a crucial element of sustainable cloud cost optimization solutions. 

Turning cloud cost principles and policies into code that’s integrated into the engineering process could generate almost $120 billion in value. 

Sources: Microsoft  

8. Focus on Implementing FinOps Practices  

FinOps practices unite finance, technology, and business teams to maximize the business value. By including FinOps services, organizations can clearly reduce costs, improve accountability, and enhance cloud efficiency.    

FinOps practices help the organization evaluate cost per customer, cost per API call, cloud spend as a percentage of revenue, and unit economics by workload. 

9. Automate Cloud Cost Governance with Policy-as-Code 

Cloud Cost Governance with Policy-as-Code includes Machine-Readable code, financial guardrails, and strategies to avoid cloud overspending. Governance involves setting clear budgets and automated tagging rules, limiting unused resources, and reducing cloud wastage.         

10. Continuously Review and Iterate Your Cloud Cost Strategy

As technology evolves, cloud environments continue to change. Cloud cost strategies also change with technology. The FinOps team should be open to communication. They should encourage cross-team communication to track unit economics, cost per transaction/user and feature.  

What Is the Importance of Cloud Cost Optimization? 

The primary objective of adopting cloud cost optimization is to control cloud costs. Here are the reasons why you should invest in it:  

1. Reduce cloud spending. Don’t overprovision resources. There might be cases where your storage volumes might remain unused for months or weeks.  
2. Enhance productivity. Ultimately, money saved brings more to the business productivity and profitability. 
3. Timely scaling. When the traffic is up, the systems will scale and vice-versa.  
4. CCO practices encourage the team to monitor wastage of resources and leverage automation. 

Summing Up 

Cloud cost optimization is a strategic process to reduce cloud spending in an organization while improving business efficiency. Given the complexity of cloud pricing models, controlling costs can be tricky. From identifying unused/idle resources to investing in rightsizing and auto-scaling tools, there are many cloud financial management best practices to follow.       

Beyond Key as Your Cloud Cost Optimization Solutions Partner  

Beyond Key is a leading cloud cost optimization company with more than 20 years of experience in IT consulting. With a team of certified cloud architects who are well-versed with AWS, Azure, and GCP platforms’ intricacies, we focus on a FinOps-driven services to keep burn rate in check. We support organizations with cloud optimization assessments, FinOps implementation, and workload modernization strategies across AWS, Azure, and GCP environments. 

From identifying hidden cloud wastage to implementing technical fixes and aligning cloud investment with enhanced business efficiency, our cloud cost optimization services are worth investing in. You can get your cloud optimization assessment here.  

Please check our real-world case studies and see how Beyond Key helped organizations across the globe operating in multiple industries achieve their cloud objectives.   

FAQs

1. What is cloud cost optimization?

Cloud cost optimization is the process of managing and reducing cloud spending while ensuring performance, scalability, and reliability of cloud resources.

2. Why is cloud cost optimization important in 2026?

With increasing cloud adoption and AI workloads, businesses are facing higher infrastructure costs. Optimization helps control waste and improve ROI.

3. What are the best practices for cloud cost optimization?

Best practices include right-sizing resources, removing unused instances, using reserved pricing models, automating scaling, and continuously monitoring usage.

4. What is FinOps in cloud cost management?

FinOps is a financial operations framework that helps teams collaborate on cloud spending, improve visibility, and make cost-efficient decisions.

The post Cloud Cost Optimization Best Practices to Look For in 2026 appeared first on Beyond Key.

Thousands of organizations are targeted by attempted cyberattacks every day, and many don’t know they are vulnerable until a breach has happened. 

A good penetration testing methodology helps companies find and fix vulnerabilities before hackers can exploit them. 

The IBM Cost of a Data Breach Report 2025 said the average global cost of a data breach was $4.44 million. Organizations that performed structured security testing saved an average of almost $1.9 million compared to organizations that did not.  

For organizations serious about cybersecurity, it is important to have a clear understanding of how penetration testing works. Penetration testing awareness is not enough; business needs to understand the process, methodologies and benefits of penetration testing in order to proactively improve their security posture.  

What Is Penetration Testing Methodology?  

A penetration testing methodology is a structured, repeatable framework that ethical hackers and security analysts use to conduct a pen test. It decides what gets tested, how it gets tested, and what is done with the results.   

Without a defined methodology for penetration testing, testing becomes inconsistent; important attack surfaces are missed, and the final report has little actionable value. A strong framework ensures that each engagement is thorough, defensible, and tied to actual business risk. 

The global penetration testing market is projected to grow at a CAGR of 11.60% and reach $7.41 billion by 2034. This is mainly due to organizations realizing that ad-hoc security checks are simply not enough anymore.  

The Most Widely Used Penetration Testing Frameworks  

Several frameworks have been adopted widely in the industry. They have different purposes. Experienced teams often combine them depending on the scope of the engagement.   

PTES: Penetration Testing Framework   

PTES is the most practitioner-oriented framework out there. It breaks a pen test down into seven phases which are pre-engagement interactions, intelligence gathering, threat modeling, vulnerability analysis, exploitation, post-exploitation, and reporting. It’s not about following the rules; it’s about mimicking the way real-world attacks occur. The entire standard is available at pentest-standard.org.   

NIST SP 800-115   

This document is published by the National Institute of Standards and Technology (NIST) as the U.S. government’s official guide for information security testing and assessment. It’s especially helpful to organizations that are trying to align their testing practices to federal requirements. NIST breaks down testing into five core phases: Planning, Information Gathering, Vulnerability Analysis, Exploitation, and Post-Testing Activities.   

OWASP Testing Guide   

The OWASP Web Security Testing Guide (WSTG) is a security resource for web applications. It includes 91 purpose-built test cases for authentication flaws, injection vulnerabilities, session management weaknesses, and more. This will be very crucial for teams performing web application penetration testing.  

MITRE ATT&CK    

MITRE ATT&CK is a knowledge base of tactics, techniques, and procedures of real attackers. It’s not a guide for testing step-by-step, but it’s a great resource for threat modelling and making sure your test is emulating real attacker behavior over hypothetical situations.   

OSSTMM  

The Open-Source Security Testing Methodology Manual is about measuring real security, not just finding vulnerabilities. Particularly suited for network and physical security assessments.   

No one framework covers everything. Typically, a mature approach to pentesting methodology involves a combination of PTES or NIST for structure, OWASP for web applications and MITRE ATT&CK for threat intelligence.  

The Key Phases of Penetration Testing  

Phase 1: Pre-engagement & planning   

All pen tests begin here. Define scope, objectives, ground rules and legal permissions before any technical work. This helps keep the engagement focused and ensures both the testers and the client are in agreement on what will be done. One of the most common reasons for misleading or incomplete results in pen tests is skipping this phase.  

Phase 2: Reconnaissance (Information Collection)   

This stage consists of passive and active research on the target. Testers will look for IP ranges, domain names, employee information, technology stacks, and possible entry points. The goal is to understand the target as a real attacker would before launching a real campaign. 

Phase 3: Enumeration and Scanning 

Testers probe the target environment to discover open ports, running services, operating system versions, and known vulnerabilities. Common tools in this phase include Nmap, Nessus, and Burp Suite. 

Phase 4: Exploiting 

This phase involves performing simulated attacks. Testers try to leverage their findings not to do harm, but to show what might actually happen. Examples include SQL injection, privilege escalation, credential stuffing, or the exploitation of misconfigured cloud services. Here the difference between manual and automated testing is clear; automated tools can quickly find common problems, but manual testing exposes logic flaws and sequences of vulnerabilities that no scanner ever catches.   

Phase 5: Post-Exploitation   

What could an attacker really do once inside? Post-exploration considers lateral movement, how data could be exfiltrated, and the actual blast radius of a breach. This phase typically identifies the most important business risks that justify the entire engagement.   

Phase 6: Reporting and Remediating   

Clients actually use well-written reports. An executive summary, a technical analysis of each finding, severity ratings, evidence and clear remediation steps prioritized by business risk the aim is not just to enumerate the vulnerabilities but to provide security and development teams with a pragmatic road map to fixing them.  

Types of Penetration Testing Engagements  

There is no one right answer to choosing a pentesting methodology. It depends on what you’re trying to break into. If you were trying to secure a physical building, you wouldn’t use the same tactics to test the front door locks as you would to audit the security guards or look at the basement blueprint. Different tests look for completely different bugs:  

• Network Penetration Testing: This is your digital perimeter test. It’s all about hammering on your firewalls, routers, VPNs, and core network infrastructure to see if an outsider can break into your internal systems.  
• Web Application Testing: The focus here is on the software. Pentesters leverage coding mistakes such as the classic OWASP Top 10 vulnerabilities and manipulate the business logic of the application to do things it was never meant to do.  
• Mobile Application Testing: Mobile application testing is different because the code is on the user’s device. This testing targets platform-specific risks unique to the iOS and Android ecosystems. See mobile application penetration testing.  
• Cloud Penetration Testing: Instead of looking for broken code, this specialized test looks for shaky identity and access management (IAM) rules, dangerous cloud misconfigurations, and exposed APIs across AWS, Azure, and GCP. Explore cloud penetration testing in depth. 
• Social Engineering Testing: Lastly, this test doesn’t concern itself with hardware and software and goes for the easiest exploit of them all, human nature. It gauges how susceptible your team is to handle the workflows, by way of simulated phishing emails or pretexting phone calls.  

Best Practices for a Reliable Penetration Test  

The difference between penetration testing and vulnerability scanning is significant, vulnerability scanners identify potential issues; pen testers confirm and exploit them. 

Why Certifications Matter in Pen Testing  

The credibility of a penetration test is only as good as the team conducting the test. Industry certifications like OSCP (Offensive Security Certified Professional), CEH (Certified Ethical Hacker) and CREST are validated by technical competency and professional standards.   

Our security analysts have OSCP, CEH, and CREST certifications and hands-on experience in critical vulnerability assessments and penetration testing projects. We’ve worked on hundreds of engagements for companies across the UK, Europe and the US, mainly on manual testing that finds things that automated tools miss.   

We have also presented this in practice with our VAPT case study for a U.S. based e-commerce client where structured vulnerability assessment and penetration testing led to a 40% reduction in security related costs. 

Conclusion 

A penetration testing methodology is not just a process document; it is the basis that will determine whether your investment in security will yield real risk reduction, or just a report that collects dust on a shelf. Frameworks like PTES, NIST SP 800-115, and OWASP provide the structure. The verdict is provided by trained certified testers. They’re an honest, defensible snapshot of where you are together.  

And if you’re wondering if your current approach to security testing is really thorough enough, well, there’s a question worth exploring. 

FAQs 

1. What is Penetration Testing Method? 

A penetration testing methodology is a structured framework for how a pen test is planned, executed and reported, ensuring every engagement is consistent, thorough and tied to real business risk. 

2. What are the main phases of penetration testing?  

Most pen tests have 6 phases. Pre-Engagement, Reconnaissance, Scanning & Enumeration, Exploitation, Post-Exploitation, and Reporting. Each phase builds on the previous one to simulate a real attacker attacking your environment. 

3. What is the best penetration testing framework? 

There is no one “best” framework. PTES is the most practitioner focused NIST SP 800-115 fits the compliance driven environment. OWASP is the standard for web application testing. Most professional teams use two or more depending on the scope. 

4. What is the frequency of penetration testing? 

At least annually, or preferably after every major code release, infrastructure change or cloud migration. Threat landscapes change fast, and a single annual test only gives you a point-in-time snapshot. 

Want to know where your real security gaps are?

For further reading, explore our related content: 

• Top 10 Penetration Testing Companies in 2026 
• What Is the Primary Goal of Penetration Testing? 
• Cloud Penetration Testing Guide 
• Manual vs Automated Penetration Testing 

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