AI summarized from verified sources
Google makes data analysis easier through conversation
Find data answers in natural language without writing SQL.
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Key Points
- 1Conversational analytics expands in BigQuery
- 2Lakehouse queries span multiple clouds
- 3Looker embedded version is GA
- 4New agents support data operations
On June 15, Google Cloud announced expanded conversational agents for BigQuery, Lakehouse, AlloyDB, Spanner, Cloud SQL, and Looker. Users can ask questions in natural language and move from analysis to root-cause checks and dashboard summaries more easily.
What changed
Google Cloud announced expanded conversational agents across BigQuery, Lakehouse, several databases, and Looker. Users can ask questions in natural language and move into analysis, summaries, and root-cause checks more easily.
Why it matters
Data analysis has often been limited to people comfortable with SQL and tool-heavy workflows. This update lowers the barrier so more business users can work with data directly through conversation.
Impact for users
It should make pre-meeting checks, dashboard reading, and issue triage faster. Cross-cloud querying in Lakehouse is especially useful for companies that want insights without moving data around.
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