From raw columns to shared understanding
Step by step — exactly what happens under the hood.
When you upload a dataset, DataLens creates a dictionary entry for every column — with inferred type, sample values and statistics.
The AI engine suggests plain-language definitions for each column based on the column name and sample data. Accept or edit.
Layer in business definitions, acceptable value ranges, PII flags and data owner assignments.
Tag columns (e.g. "financial", "customer", "derived") for discoverability and governance reporting.
Dictionary is available to all workspace members. Acts as living documentation — always current.
Built for real workflows
Not just a feature — a step change in how your team works with data.
Definitions live alongside the data. No more hunting through Confluence or emailing the data team.
Mark sensitive columns explicitly. Feeds directly into access control and governance reporting.
AI generates first-draft definitions you review and approve — not write from scratch.
See it in action.
Request a demo and we'll walk you through this feature with your own data in mind.