Written by Dan Knott, Data and AI Practice Lead 

Technology alone won’t transform your organisation. If it did, every business with a reporting tool, a data warehouse or an AI pilot would already be an industry leader. 

You can’t buy a data culture. And that’s exactly where most organisations go wrong. 

They expect that a platform, like Microsoft Fabric (powerful as it is), will magically create alignment, consistency, and better decision making. But real cultural change doesn’t come in a box. It comes from people: how they work, how they think, and how they use data to drive the business forward. 

In this follow-up to our Blueprint of a Great Data Culture, I’ll delve into the practical steps IT leaders can take to embed data into the fabric of their organisation and highlight the common pitfalls that stall so many initiatives. 

The 3 Key Mistakes That Hold Businesses Back 

Many organisations that think they’re becoming data driven, but in reality, never quite get there. There are a few common pitfalls that I’ve seen time and time again.  

1. Treating data culture as a technical project: Data culture isn’t a reporting rollout, a BI project, or an AI pilot. Those are outputs. Culture should be embedded in the way of working.  
2. Missing business involvement from the start: Building a data culture will not be possible unless everyone in the business is bought in. Without cross department input, teams are not invested and it can feel like another unnecessary process. 
3. ‘This is how we’ve always done it’ mentality: Gutfeel decisions. Spreadsheets saved on desktops. Siloed versions of the truth. Culture change means letting go of old habits, and that can’t happen without intentional support. 

Practical Steps to implement a strong data culture  

Creating a data culture begins long before platforms and dashboards. IT leaders must shape and secure a business-wide mandate for change. Here’s how: 

Step 1: Start with Leadership and Vision 

Senior leaders must be the ones driving and backing the cultural shift. Leadership support empowers IT teams by enabling them to work seamlessly without resistance. They also encourage the company-wide adoption that is critical for success. 

Key actions to take: 

Build a shared vision with the C-suite 

• Run a workshop with key business leaders to help align data initiatives with business goals. Consider cost reduction, customer growth, compliance and operational efficiency. 

Translate the vision into a business-backed roadmap 

• Build a structured roadmap that demonstrates key milestones, from quick wins to long-term business outcomes. Each milestone should be measured and tracked to a KPI to ensure successful review.  

Secure executive sponsorship 

• Dedicated exec sponsor(s) should champion the change publicly in various forums to reinforce expectations as well as model the intended behaviours you want employees to adopt. They should also ensure that there are adequate resources allocated to the initiative.  

Step 2: Establish a Single Source of Truth 

Every organisation struggles with spreadsheet chaos. It’s easy for different teams to manipulate the same numbers in different ways, potentially coming to wrong conclusions. Most critically, having a trustworthy data platform lays the groundwork for AI readiness. If the data isn’t accurate and trustworthy, neither will the AI be. It’s that simple. 

Key actions to take:  

Identify and prioritise core data domains 

• Start with areas where inconsistent data causes the most friction. This could include customer master data, finance/forecasting, marketing attribution and service delivery metrics. Then run a data audit to understand where the data lives, who owns it, how many versions exist, and how it’s currently used (and misused). 

Design a governed, accessible architecture 

• This typically includes implementing a unified data platform such as Microsoft Fabric, defining ownership and ingestion processes, as well as controlling access where necessary. There should also be a built-in data quality and validation processes. But governance doesn’t have to be heavy-handed. You need to start with core principles, not long policy documents. 

Clean the data before surfacing it 

Before exposing dashboards, you should… 

• Fix critical data quality issues 

• Validate key metrics with business users 

• Document known limitations 

• Test data accuracy with “friendly sceptics” in the business 

Step 3: Build Data Literacy Across the Business 

A sophisticated data platform is meaningless if people don’t know how to use it, or don’t share the same language. Data literacy isn’t about teaching everyone Python or SQL. It’s about ensuring people can understand the metrics, interpret the data, and apply insights in their role. 

Key actions to take:  

Create a business glossary 

Start with essential, high-impact terms such as:  

• What does “Gross Margin” mean here? 

• When does an Opportunity become Qualified? 

Co-create definitions with each business function. Host them in a central, easy-to-access place. 

Run role specific training 

Avoid generic “Power BI training for everyone,” And instead design learning journeys by role: 

• Exec team: reading dashboards, challenging assumptions 

• Sales: understanding pipeline metrics 

• Marketing: attribution logic, campaign performance 

• Finance: forecasting and scenario modelling 

• IT: governance, access, troubleshooting, lineage 

You should also make data literacy part of your company’s induction process. This makes data driven behaviour a default, not a bonus. 

Encourage “data ambassadors” 

Identify individuals who naturally ask good questions and understand the tools. These are people who can influence their peers and support with questions. 

Step 4: Embed Data into Everyday Behaviour 

A culture only forms when new behaviours become habit. It needs to be embedded in employees’ regular ways of working to be effective.  

Key actions to take:

Integrate data into existing rituals 

Rather than creating new processes: 

• Use dashboards for monthly performance reviews 

• Review KPIs at weekly team meetings 

• Incorporate data into quarterly planning 

• Make reports the default starting point for decision making 

Standardise on agreed tools and dashboards 

• Nothing kills culture like fragmentation. Ensure your entire organisation is aligned by making it clear which dashboards are “the single source of truth” and decommission redundant spreadsheets and shadow systems. 

Use Power BI and Fabric to democratise access 

• Give teams self-serve analytics where appropriate, but with standardised definitions, pre-built data models, and simple, clear visualisations. Self-serve only works when the foundation is governed. 

Step 5: Start Small, Celebrate Wins, and Iterate 

Cultures shift gradually. Start small, and celebrate where it is going well. 

Choose small, visible use cases first 

Good examples: 

• Reducing forecast discrepancies between Sales and Finance 

• Improving campaign reporting accuracy in Marketing 

• Reducing manual spreadsheet reconciliation in Operations 

Quick wins build belief. 

Create a feedback loop 

You need that feedback loop… a great data culture never stands still. 

Implement: 

• Monthly data council meetings 

• Dashboards tracking data quality 

• Suggestion channels 

• Regular retrospectives after report launches 

Publicly celebrate success stories 

People adopt what they see being rewarded. You should showcase wins including: Who used data to solve a problem, Where a decision changed because of insight and what the key outcome was.

Iterate continuously 

Your data culture is a living system, not a project: 

• Update definitions as the business evolves 

• Add new use cases 

• Improve data models 

• Retire reports that no longer serve a purpose 

• Continually refine governance 

Culture compounds through iteration. 

Ready to strengthen your data culture? 

If you’re looking to build a data culture that drives decisions, unlocks AI readiness, and aligns your entire organisation, we can help you. Cloud Direct works with leaders who want to break through old ways of working. To build something stronger, smarter, and more sustainable.  Reach out to us using the form below.

If you’re searching for more information to help plan your AI journey, our data and AI playbook can help to guide you.

Every year, Microsoft retires a new wave of products as it accelerates its cloud-first and AI-powered roadmap. For IT leaders, these changes can directly impact security, budget planning, operational continuity, and the ability to adopt the latest Microsoft innovations. 

2026, in particular, is a year of major inflection points. Several widely deployed Microsoft platforms move into final support phases or are superseded by modern cloud equivalents. At the same time, Microsoft is combining parts of its security ecosystem. Most notably unifying Sentinel (SIEM) and Defender XDR–led operations under a single operational model. 

This guide highlights the key product changes coming in 2026, so that you can prepare for how these may affect your organisation.  

Why Microsoft End of Life in 2026 Matters for IT Leaders

End of Support isn’t just a date in a spreadsheet. It has real-world implications:

1. An increase in security risk 

Unsupported systems become immediate targets for attackers. No patches, no fixes mean just vulnerabilities waiting to be exploited. In today’s landscape, this is no longer acceptable risk; it is a board level issue. 

2. Blockers to modernisation and AI adoption 

Legacy operating systems and server platforms cannot support Microsoft’s modern technologies such as AI services like Copilot. Staying on outdated systems means you cannot use the capabilities Microsoft is investing in the most. Therefore, limiting the innovation of your organisation. 

3. Rising operational cost and technical debt 

Legacy infrastructure becomes increasingly expensive to maintain, whether due to bolt on security solutions, extended support costs, or complex workarounds needed to keep ageing apps running. 

2026’s Most Impactful End of Support Milestones 

Mark your calendars. These are the product changes you need to know. 

Windows 10 

Deadline: 2026 marks the end of Year 1 ESU 

While the primary Windows 10 end of support (EOS) date landed in 2025, many organisations will rely on Extended Security Updates (ESUs) through 2026. Crucially, 2026 is Year 1 of ESU, which is the lowest cost year before fees escalate significantly. 

Remaining on Windows 10 means organisations shoulder increasing risk and cost. It also limits access to new capabilities delivered only on Windows 11, including Copilot and Intune management features. 

For IT leaders, 2026 is the final window to: 

• Complete fleet migration to Windows 11 

• Retire non-compliant hardware 

• Evaluate Windows 365 for legacy application continuity 

• Refresh endpoint standards and Zero Trust policy enforcement 

Windows Server 2016 

Deadline: EOS 12 January 2027. 2026 is the final full year to migrate 

Windows Server 2016 moves into its last full year of support in 2026, ahead of its hard EOS on January 12, 2027. Despite its age, it remains heavily deployed across midmarket and enterprise environments, often underpinning identity, file services, and key business applications. 

Outdated servers introduce material risk into the environment. Particularly when used for Domain Controllers or critical application workloads. As a result, 2026 becomes the decisive year for planning and executing migrations. 

Recommended priorities include: 

• Assessing which workloads can be rehosted or modernised in Azure 

• Upgrading or redesigning domain controller architecture 

• Planning dependency remediation for older line of business apps  

SQL Server 2016 

Deadline: EOL on July 14, 2026 

SQL Server 2016 remains common across operational reporting systems, ERP backends, and custom applications. Its hard deadline of 14 July 2026 means organisations must accelerate planning now, particularly where refactoring or cloud migration is required. 

Migrating from SQL 2016 opens the door to: 

• Azure SQL Managed Instance 

• Azure SQL Database PaaS 

• SQL Server 2022 (for on-prem regulatory or isolation requirements) 

• A more modern data platform aligned to Azure, Fabric, and AI initiatives 

SharePoint Server 2016 

Deadline: EOL on July 14, 2026 

On premises SharePoint is still widely used in organisations with complex intranet structures, document retention requirements, or customised workflows. These organisations face rising operational risk if they are not quick to react. 

Migrating to Microsoft 365 brings significant benefits. Including more secure collaboration, modern intranet capabilities via Viva Connections, Power Platform based workflow automation, and reduced infrastructure overhead. 

Office LTSC 2021 

Deadline: EOL on October 13, 2026 

This is important for organisations that deliberately avoided cloud subscriptions. Office LTSC 2021 was often purchased as the “safe”, perpetual alternative to Microsoft 365. But its end of support on 13 October 2026 forces a strategic decision: 

• Move to Microsoft 365 Apps for Enterprise 

• Or accept major compatibility, security, and integration limitations 

More importantly, Office LTSC will not benefit from the rapid innovation cycle. Meaning your organisation will miss out on the latest AI and collaboration offerings that are central to Microsoft’s ecosystem. 

Security Modernisation: Sentinel to Defender Portal Consolidation 

This isn’t a product retirement, but it is a major operational shift. 

New sunset date: 31 March 2027 

Microsoft has extended the retirement date of the classic Log Analytics based Sentinel portal in favour of the unified Defender security portal, from 1 July 2026 to 31 March 2027. This allows customers to additional time to seamlessly migrate.  

This change means: 

• Investigation, hunting, and response become Defender centric 

• Sentinel continues as a SIEM, but its UI moves into Defender 

• SOC teams must retrain on new workflows 

• Tooling consolidation may reduce duplicated platforms 

This aligns with Microsoft’s broader strategy: unified SIEM and XDR experiences under Defender, reducing complexity and improving correlation across identity, endpoint, network, and cloud workloads. 

Conclusion: 2026 Is the Year to Reduce Risk and Remove Roadblocks 

The Microsoft products hitting end of support, or undergoing major strategic repositioning in 2026 represent some of the most widely deployed technologies in corporate IT. 

Addressing them means reducing security risk, unlocking AI capabilities, and freeing your organisation from legacy technical debt. 

Acting on these changes in 2026 will set the foundation for a more innovative future for your organisation.  

Not sure where to begin? Reach out to one of our experts using the form below. Tell us the technology you are concerned about and we will be in touch to discuss a solution right for you.

Are you getting the full value from the Microsoft 365 licenses you’re already paying for?

Licensing for Microsoft 365 (M365) is no longer just a question of cost control. It’s a strategic lever for business productivity. As the suite of Microsoft offerings evolves, so too must the approach organisations take to managing their licensing. We don’t need to tell you that getting this right impacts the capabilities your teams have at their fingertips. Not to mention the ability to scale and secure your business with confidence.

Beyond the Price Tag: Why Licensing Matters

Many organisations focus solely on licensing as a cost to be minimised. While cost efficiency is important, the true value of smart licensing management goes far deeper. It’s about reducing complexity, avoiding shadow IT and most importantly ensuring every user has the tools they need to do their best work.

Misaligned or fragmented licensing can lead to significant challenges, specifically:

• Under-licensing: Where users lack access to key features, resulting in productivity gaps, workarounds, and compliance risks.
• Over-licensing: Where organisations pay for features and services their users never touch.
• License sprawl: Having multiple SKUs scattered across the environment, leading to administrative headaches and missed opportunities for bundling.

Mapping Needs to Capabilities: The Power of the Right License

Not all users are created equal. An executive, a developer, and a frontline worker each have distinct needs and workflows. Microsoft has responded by offering a portfolio of flexible, feature-rich licenses such as Microsoft 365 E3, E5, and Business Premium (BP). By aligning licenses to actual user requirements, you can strike the ideal balance between cost and capability.

• M365 E3 delivers a comprehensive suite for knowledge workers, with core Office apps, cloud storage, advanced security, and device management.
• M365 E5 layers on advanced security, compliance, analytics, and voice capabilities. These are particularly critical for heavily regulated industries or those facing sophisticated cyber threats.
• Business Premium is tailored for small and medium-sized organisations, offering robust productivity, security, and device management features for up to 300 users.

Simplifying with Bundles: Consolidating SKUs for Maximum Value

One of the most overlooked opportunities in licensing management is SKU consolidation. Instead of managing a patchwork of add-ons and standalone products, you can often bundle multiple solutions into a single, cohesive license. For example, E3 and E5 licenses include a broad range of capabilities under a unified subscription.

This consolidation brings several advantages:

• Simplified administration: Fewer SKUs mean less time tracking entitlements, reconciling renewals, or troubleshooting issues related to access rights.
• Streamlined support: With core services under a common umbrella, support and escalation paths become simpler and more effective.
• Better user experience: Users benefit from a seamless, integrated ecosystem, reducing friction and enabling collaboration.
• Cost efficiency: Bundles often deliver more features for less compared to purchasing standalone products piecemeal.

Therefore, it’s essential to regularly audit your licensing estate and identify opportunities to migrate fragmented products to consolidated E3, E5, or Business Premium licenses.

Unlocking Advanced Capabilities: E5 Security and Compliance for Business Premium

Historically, smaller organisations using Microsoft 365 Business Premium were limited in their access to advanced security and compliance tools. However, Microsoft has changed the game: E5 Security and E5 Compliance add-ons are now available for Business Premium users.

What does this mean in practice?

• Advanced Threat Protection: Gain cutting-edge security features, like Microsoft Defender for Endpoint, identity protection, and automated investigation and response. Elevating your defence posture without migrating to enterprise SKUs.
• Comprehensive Compliance: Access to features like Insider Risk Management, Advanced eDiscovery, and Information Protection, to meet stringent regulatory requirements and proactively manage data risks.
• Flexible Scaling: As your business grows, you can seamlessly layer these add-ons atop Business Premium, ensuring your security and compliance capabilities scale in step with your ambitions.

This expansion of E5 features to BP closes the once-yawning gap between SME and enterprise security and compliance.

Best Practices for Effective M365 Licensing Management

To truly maximise the benefits of licensing, consider these steps:

• Assess User Needs Frequently: Conduct regular reviews to match licenses to evolving user roles and business strategies.
• Audit and Optimise: Identify inactive licenses, unused features, and areas for consolidation. Never pay for more than you need.
• Leverage Self-Service Tools: Use the Microsoft 365 Admin Centre and third-party analytics to gain insights and automate reporting.
• Stay Informed: Microsoft’s licensing portfolio changes rapidly. Keep up to date to ensure you’re not missing new capabilities.
• Engage with Partners: Certified MSPs and licensing specialists can help you navigate complexity, unlock hidden value, and ensure compliance.

Conclusion: Modern Licensing as a Strategic Enabler

Effective Microsoft 365 licensing is the key to unlocking productivity and innovation across your organisation. By consolidating SKUs, mapping licenses to real-world user needs, and leveraging new add-ons, businesses of all sizes can build a foundation that’s future-proof. With the right approach, M365 licensing becomes a strategic asset, driving growth, resilience, and seamless digital transformation.

Reach out to the team by filling in the form below to discuss your licensing requirements.

Introduction

Cloud adoption promises agility to build innovation in your IT Infrastructure. And while this is possible, for many organisations, the reality doesn’t match the vision. Costs spiral, security concerns grow, and IT teams become overwhelmed. Why does this happen?

The answer is simple: you need a clear Cloud Operating Model (COM) to navigate successfully to your desired destination.

Life without a COM

• Costs rise as self-service provisioning gets out of control.
• Security becomes harder to maintain as the attack surface expands.
• IT teams drown in user queries instead of driving innovation.

If this sounds familiar, it’s time to rethink your approach.

What is a Cloud Operating Model?

Microsoft defines a Cloud Operating Model as:
“The collection of processes and procedures that define how you want to operate technology in the cloud.”

In other words, it’s your blueprint for managing the operational shift from on-premises IT to cloud-based systems. It covers everything from governance and security to technology management and cultural change. As one of the longest-standing Azure Expert Managed Service Providers, we’ve based our approach to Cloud Operating Models on Microsoft’s proven best practices and tools.

The Five Pillars of a Cloud Operating Model

A strong COM isn’t one-size-fits-all, but successful models share common attributes. Here are the five pillars to consider:

1. 24×7 Operations
   Successful transformations depend on people, not technology. When you’re in the cloud, the skills your IT teams need will change dramatically. Operations shifting to 24/7 availability amplify this further as employees need to be equipped to deal with any manor of issues at any time.
2. Technology and Management
   Cloud adoption introduces scalability and flexibility, but also complexity. You’ll need new processes and tools for monitoring usage, managing virtual machines, and extracting insights from analytics. This will ensure your environment remains optimised and delivering maximum ROI for your business.
3. Strategy and Governance
   Governance, security, and compliance are non-negotiable when implementing your cloud strategy. When you shift to the cloud your network parameter expands far beyond traditional firewalls, therefore, the treat landscape increases. Adopting frameworks like Zero Trust, and leveraging tools such as Microsoft Defender can help keep your data safe and controlled.
4. Transition and Change Adoption
   Moving to the cloud successfully should be a cultural shift. Slow and mundane processes will become a thing of the past. Adoption means faster development cycles, new financial models (OpEx vs CapEx), and incorporating cloud native practices to quickly meet customer needs. However, it’s vital to manage this new pace of change effectively to be successful.
5. Account and Relationship Management
   Ongoing optimisation and stakeholder engagement ensure your cloud services deliver value. Regular reviews and proactive relationship management help maintain alignment with evolving business priorities.

Next Steps

Ready to dive deeper?

Read the full guide to discover how to build a Cloud Operating Model tailored to your business.

In ‘The Data & AI Readiness Playbook’ we explain how you can unlock the value of your business data. Quality data is crucial to the effectiveness of AI. Here we look in more detail at the importance of data culture and the practical steps you can take to build a great data culture.    

Data is perhaps the single greatest asset of the modern business and the bedrock of successful AI initiatives. But the quality of that data is critical to success.  

The ROI of investing in data quality

Already convinced of the importance of quality data? Then skip ahead to ‘Developing a great data culture’, otherwise read on.  

When we refer to quality data, we mean that it is accurate, complete, consistent, timely, valid, unique, and reliable. Armed with that, both human and artificial intelligence can arrive at the decisions that deliver real value.

Matthew Ebo is Assistant Strategic Insights Manager at Lloyds Banking Group and a contributor to ‘The Data & AI Readiness Playbook’. Matthew explains, “The cost of AI is an investment, but one that pays off in saved time, better decision-making, and automation of repetitive tasks”.  

Developing a great data culture is an investment. An investment in the raw materials for transforming how an organisation operates, competes, and grows. For the business, this can drive value in many ways: 

• Better, evidence-based decisions enabling more effective strategies, faster responses to market changes, and improved stakeholder buy-in for new initiatives. 

• Increased innovation and agility as the organisation becomes better at identifying new opportunities, anticipating trends, and proactively adapting to changes.  

• Improved operational efficiencies as data insights help identify inefficiencies and optimise processes and resource allocation.  

• Greater competitive advantage gained from better anticipation of customer needs, reaction to industry shifts, and speedier innovation.  

• Enhanced customer experience through superior analysis of customer data, to tailor products, services, and communications to better meet customer needs.  

• Boosted employee engagement as staff become more engaged, and invested in the success of the business, by using data in their roles. 

• Trustworthiness – data driven cultures tend to be open about business decisions improving trust amongst employees.

A great data culture enables smarter decisions, drives innovation, enhances customer and employee experiences, and provides a competitive edge. 

So how do you get one?  

Developing a great data culture

We know that AI initiatives are only as good as the data they access, so data quality is key – and great data follows a great data culture. 

Data quality isn’t solely the responsibility of IT: it’s everyone’s responsibility. But it is IT’s responsibility to encourage a culture in which everyone cares about data quality“, explains Dan Knott, Data & AI Practice Lead, Cloud Direct.

A great data culture is one where data is valued by an organisation and its people, becoming a key part of daily operations. Here are eight key aspects of a great data culture.  

1. Leadership commitment and example
As with most aspects of culture, data culture needs to be led from the very top. Senior management need to be actively involved in communicating the importance of data to organisational success. This needs to be supported with investment in the resources, training, and technology to support data initiatives.

2. Data-driven decision making
It needs to become the norm that decisions, at all levels, are based on data and analysis and not just intuition or hierarchy. Leadership and example are an important part of this. It also means establishing processes that make data analysis a standard part of planning, operational, and problem-solving activities.

3. Data access and democratisation
For IT this means ensuring that employees have easy, secure access to data and analytics tools. Employees should be able to freely share data internally, within appropriate privacy and security parameters, to enable collaboration.

4. Data literacy and training
Key to all this is an ongoing investment in employee’s data awareness and skills, ideally with training tailored to different roles and data personas. This should equip staff with the skills to interpret analytics, know when to use data, and to ask the right questions about data quality.

We’re looking at AI in the same way as other tools which become part of the workforce’s toolbelt, so we have to provide the same level of training for it. It’s not only imperative that the right skills are gained, but that they are regained as time goes on“, explains Mike Downing, Chief Technology Officer at insurance nonprofit WPA

5. Continuous learning and improvement
Alongside formal training initiatives, organisation’s need to develop a mindset of ongoing learning, experimentation, and adaptation – constantly utilising data to refine strategies and processes.

6. Trust in data quality
Underpinning this, there needs to be organisation-wide confidence in data accuracy and consistency. People know where data comes from and how reliable it is. This requires robust data governance, clear data lineage, and transparent processes for data validation and error correction.

7. Collaboration and communication
Success will be evidenced through open communication and collaboration around data, with teams working together to solve problems and share insights. This should be openly encouraged. It is important that this is also supported by establishing a common ‘data language’, so everyone communicates effectively.

8. Accountability and measurement
The final aspect of great data culture is one of transparency and it is an extension of point two. Clear goals and metrics are set for data initiatives, with progress tracked and results linked to business outcomes. With performance KPIs relating to data usage built into everyone’s evaluations.

Together, these elements can help you to build a great data culture that will deliver demonstrable value to your organisation and support effective use of AI.  

Next Steps

Download a copy of The Data & AI Readiness Playbook to learn more. You’ll discover how others are preparing for and using AI, and a seven-step process to unlock the value of your business data.