What Is AI Usage Data. How Enterprises Can Collect It.
Learn what AI usage data includes, how enterprises collect and track it, and why centralizing usage metrics is key to measuring AI adoption and ROI.
You can now review the activity history of any resource in the new tab of the resource detail panel.

You can now see all files available within your source folders. With file listing, view the list of files in file type storage when setting up a source/destination. To preview a file, hover over an individual file and click the preview button to preview data before you connect. The preview button will allow you to see partial file content (first 100 lines) of files listed in file type source/destination setup and source/destination detail.
Native support for writing transform code in python and javascript along with Nexla JSON.
Error data can be automatically delivered in JSON files to a location of your choice for evaluation, correction, and re-ingestion. Error files are delivered with file names [source,pub,sub]/{id}/{yyyy}/{mm}/{dd}–{error_id}.json
View the full release and other product updates here.
Learn what AI usage data includes, how enterprises collect and track it, and why centralizing usage metrics is key to measuring AI adoption and ROI.
Reusable data products unify databases, PDFs, and logs with metadata, validation, and lineage to enable join-aware RAG retrieval for reliable GenAI applications.
Governed self-service data embeds metadata controls, quality guardrails, and access policies. This enables business users to explore and transform data in no-code while preventing metric drift.