Query Builder
Query Builder visually models database tables and relationships into reusable governed datasets. Saved queries can feed Data Studio, ETL refresh, charts and dashboards.
What this feature delivers
Its product workflow handles schema discovery, table/column loading, SQL execution, row limits, ETL linking and refresh behavior. When a saved query powers an ETL, optimized data engine output and step dependencies are refreshed safely.
Visual SQL creation
Users select tables, columns, joins and filters while platform applies limits and connection parameters.
Linked ETL refresh
Saved query changes can rebuild related ETL tables and respect full-dataset step requirements.
Subject-based publishing
Queries are stored under subjects so users consume managed datasets instead of raw connections.
Use case
These steps show the need this feature solves for a real team and how it moves analysis closer to action.
Select tables
Authorized provider metadata is loaded.
Build relationships
Joins, filters, columns and limits define the query.
Publish dataset
The query is saved under a subject and becomes usable by analytics flows.
Governed and traceable flow
Query Builder balances SQL flexibility with governed dataset delivery through connection, subject and ETL refresh controls.
Which teams is this feature for?
Business users get faster answers, analysts keep quality and control, and admins manage data and access rules.
Does it work with other LivChart features?
Yes. The feature pages explain how preparation, AI, dashboards, reporting and sharing work together rather than as isolated modules.
Try LivChart with your own data
Connect Excel, CSV or database data and test AI charts, dashboards and reports with a local-first architecture.