developing-with-bigquery

Included with Lifetime

$97 forever

A repository of BigQuery-specific logic, knowledge, and specialized standards. Use this skill whenever you are doing anything with BigQuery, including: 1. BigQuery query optimization 2. BigFrames Python code 3. BigQuery ML/AI functions.

General

What this skill does


This skill provides comprehensive guidance for BigQuery services, optimizations,
and data handling. It acts as a routing table for specialized BigQuery topics.

> [!IMPORTANT] For general standards on running BigQuery in notebooks (SQL
> cells, `export` keyword), see `@skill:notebook-guidance`.

> [!IMPORTANT] You MUST check the data size before deciding on which libraries
> to use. Use the data size to justify your decision.

Refer to the following resources for expert guidance on specific BigQuery
features:

### 1. Query Optimization

Performance and efficiency guidelines for BigQuery SQL. Includes rules for
column pruning, pushdown, and materialization strategies. - **Guide**:
[OPTIMIZATION.md](references/OPTIMIZATION.md)

### 2. BigFrames (BigQuery DataFrames)

Guidelines for generating valid BigFrames code for data manipulation, model
development, and visualization. - **Guide**:
[BIGFRAMES.md](references/BIGFRAMES.md)

Bigframes should be the default library/tool as it is more efficient than using
the BigQuery Python client library.

### 3. BigQuery ML & AI Functions (BQML SQL)

Usage rules and syntax standards for all BigQuery AI/ML functions via SQL
(Forecasting, Generative AI, Classification, etc.). - **Guide**:
[BQML.md](references/BQML.md) - **Functions Reference**: -
[AI.FORECAST](references/ai-forecast.md) -
[AI.EVALUATE](references/ai-evaluate.md) -
[AI.GENERATE_TABLE](references/ai-generate-table.md) -
[AI.GENERATE_EMBEDDING](references/ai-generate-embedding.md) -
[Remote Models](references/remote-models.md)
[CONTRIBUTION_ANALYSIS](references/ml-contribution-analysis.md)
[VECTOR_SEARCH](references/vector-search.md)

### 4. Notebook SQL cells

Refer to `@skill:notebook-guidance` for standards on running BigQuery in
notebooks.

Files: 11

Size: 27.2 KB

Complexity: 56/100

Category: General

Source: https://github.com/gemini-cli-extensions/data-agent-kit-starter-pack/tree/main/skills/developing-with-bigquery

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