Data Outlook 2026: The Rise of Semantic Spheres of Influence

In 2024, the elephant in the room was how generative artificial intelligence seized the conversation. In 2025, the dialog shifted to agents and the question of whether there’s an AI bubble happening in our midst. But as we noted, AI’s taking of the limelight shined a new spotlight on the importance of having good data, and so last year, we forecast that data would have a renaissance.

Spoiler alert: Though having good data is an essential first step, AI models need the right data, and that’s where the focus will shift this year. In the words of Cindi Howson, semantics are sexy again.

So was there a Data Renaissance last year? On the main stage at AWS re:Invent, Garman’s keynote had just one data-related announcement: the unveiling of a long-awaited Database Savings Plan that met even tough critic Corey Quinn’s approval. But AWS’ off year for data doesn’t tell the whole story. PostgreSQL had a banner year, and so did the integration patterns of Zero-ETL, first popularize by AWS to populate its Redshift data warehouse, but now extended by Microsoft, Databricks, and Snowflake to blur the line between operational databases and data lakehouses. And who could ignore the sudden emergence of MCP, showing that the AI world is taking data seriously. But does a string of announcements signify that a renaissance happened? Reality isn’t black and white.

But for the year ahead, the need for AI, not simply to have good data, but the right data, is making semantics (in the words of Cindi Howson) sexy again. SAP is making semantics available, on its own terms. Microsoft is forging ahead with ontology – not just what the data means, but where does it fit in the context of the organization? And Snowflake has announced a cross-vendor initiative for the exchange of semantic metadata.

Click here, not just to get the full treatment, but a (hopefully) objective assessment of how close or badly off our 2025 predictions were. Happy new year!