data-autocleaning

Automate data quality checks and transformations for BigQuery and GCS pipelines.

161|37|Updated Apr 2, 2026

Search Tags:#transformation #bigquery #data-quality #data-cleaning #data-profiling #gcs #dataplex

Ready to run

npx skills add https://github.com/gemini-cli-extensions/data-agent-kit-starter-pack --skill data-autocleaning

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-autocleaning
Source: https://github.com/gemini-cli-extensions/data-agent-kit-starter-pack/tree/main/skills/data-autocleaning
Command: npx skills add https://github.com/gemini-cli-extensions/data-agent-kit-starter-pack --skill data-autocleaning

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Automated data quality checks and transformations for data pipelines that source data from BigQuery and Google Cloud Storage (GCS). It ensures consistent profiling, cleansing, and schema mapping across the data lifecycle, reducing manual effort and error-prone handoffs.

Core Features & Use Cases

Automated data profiling and cleansing across BigQuery and GCS sources.
Deterministic transformation templates to standardize schemas and normalize data.
Schema mapping guidance and workflow for data ingestion, movement, and deployment to downstream systems.

Quick Start

Provide the dataset details and run the autocleaning workflow to start profiling and generating transformations.

Frequently Asked Questions about data-autocleaning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate data quality checks for BigQuery pipelines?▼

Automate data quality for BigQuery pipelines by running a deterministic workflow that handles data ingestion, profiling, cleansing, and schema mapping. This enforces consistent quality verification and reduces manual transformation errors across sources.

What is data profiling and how does it work with GCS and BigQuery?▼

Data profiling with GCS and BigQuery is a process that analyzes source datasets to generate statistics and determine data quality. It uses Dataplex-based profiling to assess data structures and guide subsequent automated cleansing rules.

Can I standardize schemas and normalize data sourced from Google Cloud Storage?▼

Yes, you can standardize schemas and normalize data sourced from Google Cloud Storage. The workflow uses deterministic transformation templates to map schemas and normalize data, ensuring consistency for downstream systems and deployment.

What's the best way to clean and transform BigQuery data without manual handoffs?▼

The best way to clean BigQuery data without manual handoffs is using a guided autocleaning workflow. It enforces deterministic transformations and end-to-end quality verification, reducing error-prone handoffs across the data lifecycle.

Do I need Dataplex to run data cleansing workflows on BigQuery?▼

Dataplex is required for data profiling within this cleansing workflow. The automated pipeline relies on Dataplex-based profiling to analyze datasets and generate the guided cleaning rules needed for transformations.