In our recent webinar, we explored the Microsoft ecosystem for 2025. Now, we want to dive deeper into one of the most critical aspects of this future landscape: the evolution of data management. As Marton Marek, our Data & AI Practice Lead, highlighted throughout the discussion, organisations face unprecedented challenges and opportunities in how they collect, process, analyse, and leverage data.
With the Microsoft ecosystem processing over 2.5 exabytes of data daily, having a strategic approach to data management isn’t just beneficial—it’s essential. Let’s explore the key trends and capabilities that will define data management in 2025.
The Explosion of Real-Time Insights
The traditional approach to data management has relied heavily on centralising information into data warehouses and building static dashboards for operational reporting. However, this model is rapidly changing.
“What we saw towards the end of last year is the beginnings of really moving away from end-users jumping into dashboards to look at these trends or static dashboards on a weekly or even daily basis,” Marton points out. Instead, we’re moving towards a notification-based approach that monitors live data and alerts users when specific benchmarks are met or critical events occur.
This shift represents a fundamental change in how organisations interact with their data. Rather than requiring users to regularly check dashboards that may show no significant changes, the system proactively notifies them when there’s something worth their attention. This allows for faster responses to emerging trends and more efficient use of analyst time.
We’re also seeing increased uptake in streaming data, real-time event-based analytics, and IoT sources. These technologies are becoming more accessible and integrated, enabling organisations to make decisions based on what’s happening now rather than what happened yesterday.
The Convergence of AI and Analytics
Perhaps the most transformative trend for 2025 is the deep integration of AI into data analytics processes. We’re moving beyond descriptive analytics (what happened) to predictive analytics (what might happen) and even prescriptive analytics (what should we do about it).
Marton explains that “we’re now starting to look at predictive analytics or even prescriptive analytics that provide us insights into not only what may happen based on the data that we’ve collected, but what can we do about it.” This represents a paradigm shift from reporting to actionable intelligence.
Machine learning models are becoming easier for businesses to develop and use as part of their analytics strategy. With tools like Microsoft Fabric, organisations can provision machine learning models using natural language queries, making advanced analytics accessible to business users without deep technical expertise.
This convergence is also enabling language-driven analytics, where users can ask questions of their data in plain language and receive insights without needing to understand complex query languages or data structures.
Unified Data Management
The third major trend we’re observing is the unification of data management tools and approaches. Instead of deploying multiple disconnected solutions, organisations are moving towards integrated platforms that handle everything from ingestion and transformation to governance and security.
“We’re seeing a lot of unification in the technology and the approach to data management,” Marton notes. “There’s a tight-knit integration between fabric and Purview that’s going to continue and be enhanced in 2025.”
This integration is crucial for organisations looking to implement comprehensive data strategies. By centralising data management functions, companies can ensure consistent governance, reduce redundancies, and create more efficient workflows.
Microsoft Purview, in particular, has evolved significantly into a more powerful and user-friendly solution that integrates seamlessly with Fabric. Together, these tools provide a strategic foundation for data management across the organisation.
The Democratisation of Data
The final key trend for 2025 is the democratisation of data—shifting responsibility and accountability for data from IT departments to business units while providing the tools and governance frameworks they need to succeed.
Marton describes this shift: “We’re seeing more and more of this push back to the business from an accountability perspective.” This doesn’t mean abandoning IT oversight but rather creating a process where validated data assets can be managed by the business units that use them most.
Self-service tools like Copilot and other language-driven interfaces are making it possible for business users to analyse data, create reports, and even build machine learning models without extensive technical training.
This democratisation is changing how organisations structure their data teams and allocate responsibilities. While IT may retain control of the infrastructure and governance frameworks, business units can take ownership of their data domains and use them to drive decision-making.
Preparing Your Data Foundation for AI
As organisations look to leverage AI capabilities, having a solid data foundation becomes increasingly important. Marton emphasises that “it’s important to set the foundations in the right way… a lot of it relies on accurately triaged data.”
Before deploying AI workloads, organisations should ensure they have:
- High-quality data that has been properly cleansed and validated
- Clear governance frameworks that define who can access what data and for what purposes
- Unified data management approaches that eliminate silos and provide a comprehensive view
- Data cataloguing and classification to identify sensitive information and manage compliance
- Benchmarks for success to measure the impact of data-driven initiatives
While it’s natural to want to jump straight into AI applications, establishing these foundations first will lead to more successful outcomes and more accurate models.
As we move further into 2025, data management will continue to evolve from a technical function to a strategic capability. The organisations that succeed will be those that embrace real-time insights, integrate AI into their analytics, unify their data management approaches, and democratise access to information.
Marton’s final advice is particularly relevant: “Whilst yes, you can certainly explore use cases, and that makes sense from a business perspective to say what’s going to make sense for us, it’s also important in parallel or even before to set up the foundations of your data management and ensure that you have high data quality.”
By focusing on these foundations while exploring the possibilities offered by new technologies like Microsoft Fabric and Purview, your organisation can position itself to leverage data as a strategic asset in 2025 and beyond.
If you’re interested in learning more about how your organisation can prepare for these changes, reach out to our data experts at Antares. We can help you assess your current data maturity, develop a roadmap for improvement, and implement the tools and processes you need to succeed in the evolving data landscape.
