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Key Trends in Data Management and Analytics in 2025
The following trends were originally presented by me at Big Data LDN in September 2024 and have since updated slightly for 2025. These trends are not in any specific order or priority.
- Gen AI everywhere – baked into infrastructure, DBMSs, tools, services, applications & processes. Also a data catalog is a key source for creating vectors for RAG which is being used everywhere. So we are likely to see a proliferation of vector databases. Also RAG is somewhat limited in that it does not show the relationships between data. So we are now seeing the emergence of GraphRAG as a stronger approach.
- AI Agents, AI orchestration for AI automation and decision intelligence for decision automation will proliferate across the enterprise as the creation of the agent enterprise starts to unfold in 2025
- Democratisation and acceleration of development is set to increase rapidly fuelled by the adoption of Generative AI co-pilots as the new UI, generation of data integration pipelines, autoML, MLOps, DataOps and Data Observability
- A federated operating model is emerging as best practice with Data & AI program office responsible for aligning projects with business strategy, coordination of multiple domain-oriented teams and creation of Data & AI communities to enable rapid development and to ensure mass contribution to common business outcomes
- A more simplified modern data architecture will emerge to support the data and AI-driven enterprise based on Common Data Fabric as a data management platform supporting multiple teams of data producers. Also the emergence of open tables (mainly Apache Iceberg), is causing Data Warehouses and Lakehouses to morph into one with support for structured, semi-structured and unstructured data as well as converged analytics e.g. traditional analytical SQL queries, in-database machine learning, graph analytics via SQL/PGQ, invocation of Generative AI LLMs from within a database via SQL, support for real-time streaming data and real-time analytics.
- Data products will be published in an internal Data & Analytics marketplace along with BI, ML models and AI-Agents, decision services and more
- Application and data integration convergence is becoming possible on a single platform as Data Fabric can now do both using GenAI
- We will move away from many stand-alone data governance tools that do not integrate very well if at all, to vendors offering complete AI-powered multi-disciplinary (DQ, privacy, access security, retention, sharing, usage) active data governance platforms. These platforms will offer a data catalog with services to continually discover and classify data in disparate data sources, to store and maintain data governance policies and provide active AI-assisted software agents to detect issues and automatically enforce policies across a distributed multi-cloud data estate.
- AI governance is now a critical success factor especially now that EU AI Act is live legislation
- There will be broad integration of GenAI, ML and analytics into processes and applications throughout the enterprise as we deploy AI-Agents everywhere. As GenAI co-pilots become the new UI, analytical systems will have to scale to support much greater concurrent usage
- Investment in ESG reporting will continue throughout 2025

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