AI tools for “bigquery”

Set up a data warehouse for Confidence experimentation analytics. Use when the user asks to connect a warehouse, set up BigQuery/Snowflake/Databricks/Redshift, or configure data connectors.

Set up BigQuery as a data warehouse for Confidence. Use when the user chose BigQuery for warehouse setup.

…Databricks, Trino, SAP HANA or Datasphere, Redshift, or BigQuery, list tables or columns, run read queries, or run DML/DDL, e.g. "run this SQL on jdbc:postgresql://… through DataRobot". If the database is already a…

…(DML/DDL) through a Snowflake, Databricks, BigQuery, SAP Datasphere, or Trino connection. Examples: "query my Snowflake data connection", "show 10 rows from SALES.ORDERS in datastore <id>", "insert…

…exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on…

…a source's tables to the user's own warehouse (Snowflake, BigQuery, Postgres, S3 and other…

…a job to an external system (Databricks, Snowflake, BigQuery, Redshift, Spark, dbt Cloud, EMR, AWS Batch, etc.) and waits for it to finish, whether as one submit-and-wait operator or split into submit +…

…is connecting to remote data to query it from GCP engines (BigQuery, Spark). Examples of when to use this: "federate my lakehouse catalog to databricks", "query data in databricks", "query data in s3", "connect to aws…

…or inspecting data assets in Google Cloud, such as: - BigQuery datasets, tables, or views - BigLake catalog or tables - Spanner instances, databases or tables - etc. 2. You need to retrieve the schema, metadata,…

…clean, correct, and efficient Dataform pipeline code for BigQuery ELT. Use this when creating or modifying Dataform pipelines, actions, or source declarations, when Dataform, SQLX, or BigQuery are mentioned in a…

…for creating, modifying, and optimizing dbt pipelines for BigQuery. Use this skill whenever user asks for generating or modifying a dbt model or project. Activate this skill when the user - Creates, modifies, or…

…quality and transformation capabilities for Dataform/dbt/BigQuery pipelines. Processes data sourced from BigQuery or Cloud Storage (GCS), applying best practices for data ingestion, movement, schema mapping, and…

Provides workflows to optimize BigQuery environments (capacity planning, editions), storage assets (partitioning, clustering, storage lifecycles, billing models), and SQL queries. Use when optimizing cost, modeling…

…analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when interpreting…

Provides guidelines and best practices for querying BigQuery property graphs and semantic graphs: native GQL (Graph Query Language) pattern matching, multi-hop and variable-length paths, aggregation, top-N, path…

…selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATION_SCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools,…

Provides an end-to-end journey for authoring a BigQuery property graph from your tables or from a model document/diagram (an ER diagram, an ontology, a semantic model): dataset discovery, candidate relationships…

Discovers and inspects BigQuery Data Transfer Service (DTS) configurations. Use this to identify existing ingestion pipelines and extract datasource or transfer config metadata for data pipelines. Use when a user asks…

Generates Python code using BigQuery DataFrames (BigFrames). Use by default for any Python data task involving BigQuery, including data processing, analysis, and machine learning. Don't use for SQL-first workflows or…

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or…