About NextTables

Data always flowed one way. The business always needed it to go both ways.

When a classification is missing, a mapping is wrong, or a hierarchy needs to change within the data & analytics platform business teams can't wait for a pipeline. They export to Excel because there's no other way to contribute what they know. That gap between what the business needs to do and what the data and analytics platform allows them to do, that's what drives us. We built NextTables to close it.

About NextTables

Data always flowed one way. The business always needed it to go both ways.

Where we come from

Every project. The same gap. A different workaround.

We come from enterprise data warehouse projects, SAP Business Warehouse (BW), large-scale analytics implementations, environments where data models are complex and the stakes are real. In project after project, the same moment arrived: a table that needed to be maintained by the business. A cost centre mapping. A product classification. A hierarchy that only the business could define.

Every project team found a way to make it work, a custom app or an Excel upload of some kind. Resourceful solutions built under real deadlines. But none of them were designed to last. We saw this pattern often enough to recognize something bigger: this wasn't a project problem. It was an opportunity to build a lasting solution.

The gap followed the data

From on-premise to the cloud. Τhe same problem, everywhere.

As enterprise data moved to cloud platforms, SAP Business Data Cloud, Databricks, Microsoft Fabric, Snowflake and others, we expected the gap to close. It didn't. New platforms, new architectures, the same reality: business teams still had no governed way to maintain the data that drives their analytics and AI. So we rebuilt. From the ground up.

Where we're going

Our vision is a world where maintaining enterprise data is as natural as asking a question, and as safe as it needs to be.

We see a future where a business user can simply describes what needs to change in plain language, and the enterprise data platform responds. Where AI agents propose updates, reclassify hierarchies, and fill structural gaps — while with validation, authorization, and a full audit trail built in by design. remain in place. Not as an afterthought. By design.

But the future of enterprise data maintenance is not automation without control. It This future is a collaboration between business teams and AI, where people define the business context, AI helps act on it, humans stay in the loop where governance requires it, and the platform enforces the rules.

Context is what makes it work. That context matters. AI does not only depend on raw tables. It depends on the mappings, classifications, hierarchies, thresholds, and business rules that explain how the enterprise actually works. NextTables is built to keeps that context inside the enterprise data platform, structured, validated, traceable, and ready for both analytics and AI.

The same guardrails that make human-led data maintenance trustworthy today are designed to extend to AI-driven interactions tomorrow. The rules stay the same even when the actor changes.