gcp-bigquery

What problem does it solve?

This Skill empowers users to design, configure, and optimize Google Cloud BigQuery for robust data warehousing, advanced analytics, and machine learning pipelines.

Core Features & Use Cases

• Dataset and Schema Design: Define BigQuery datasets and create partitioned, clustered, or standard table schemas using Terraform or SQL.
• SQL Query Optimization: Generate efficient SQL queries for analytics, funnel analysis, and sessionization, including DML statements like MERGE and DELETE.
• ML and Pipelines: Implement BigQuery ML models (classification, forecasting, clustering) and set up scheduled queries or materialized views for ETL/ELT.
• Data Loading & Security: Configure external tables, streaming inserts, and implement column/row-level security and authorized views.
• Use Case: A data engineer needs to set up a new analytics dataset in BigQuery, including defining schemas for event data, creating materialized views for daily aggregates, and securing access for the data science team.

Quick Start

Use the gcp-bigquery skill to generate a partitioned and clustered table schema for event data.