By design, Looker is the enterprise semantic platform which ensures that every data set meets a high standard of accuracy by acting as a single source of truth and providing long-term consistency of your metrics. Today, we are introducing a complement to this governed framework: self-service Explores, to accelerate high-velocity, ad-hoc analysis. Self-service Explores allows you to bring your own data directly into the Looker semantic layer, providing instant access to insights while maintaining the integrity of your existing governed data ecosystem.
Data teams often find themselves caught between two worlds. On one side, there’s the trusted, governed world of modern BI, where every metric is defined and every row is verified. Then there’s the agile, anything goes nature of spreadsheets and CSV files where you can get answers in seconds but run the risk of ending up in a siloed data vacuum.
Self-service Explores bring the value of modern, governed BI to the experimentation self-starting capability of spreadsheets, allowing anyone with the right permissions to turn a flat file into a fully functional Looker Explore in seconds. You can also import from Cloud from Google Drive and quickly transform Google Sheets data into conversational analytics. No code, no waiting — just insights.
You can drag and drop a comma separated or spreadsheet file (.csv, .xls, or .xlsx) or pull directly from Google Sheets, and Looker automatically creates an Explore. Behind the scenes, these files are securely stored in your own BigQuery instance, ensuring your data remains within your controlled infrastructure.
