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Generative AI
Cloud
Testing
Artificial intelligence
Security
July 03, 2025
Senior Architect and Subject Matter Expert in Data & AI, Sogeti
Data environments rarely evolve in a straight line. Over time, different teams make different decisions—choosing the tools, platforms, and structures that meet their needs in the moment. This works well at first, but it often results in fragmentation that’s hard to see until it starts slowing things down.
‘A Practical Guide to Data Modernization’ lays out a pragmatic approach to modernization for data leaders dealing with that kind of sprawl. It’s ideal for organizations that operate with decentralized teams, diverse systems, and increasing pressure to deliver business-ready insights. Rather than starting over, it focuses on simplifying what exists and creating a foundation for long-term scalability.
Inside, you’ll find a three-phase model that reflects today’s modernization journeys:
• Visibility focuses on mapping what exists and how data is used.• Consolidation helps reduce overlap and build shared foundations.• Activation supports teams in building new data products with less rework.
We also look at how Microsoft Fabric supports this journey – to build from what’s already in place and shift toward a setup that’s easier to scale and govern.Learn how your teams can bring alignment to scattered environments and move forward with much-needed clarity.
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