datahub-skills
NewDataHub development and interaction toolkit with connector planning, PR review, catalog search, metadata enrichment, lineage tracing, data quality management, and connection setup skills
Summary
This skill provides a comprehensive toolkit for interacting with DataHub, enabling developers to plan connectors, review PRs, search the catalog, enrich metadata, trace lineage, manage data quality, and set up connections.
- It streamlines data discovery and governance tasks directly within Claude Code.
Install & Usage
mkdir -p .claude/skillsAdd the configuration to .claude/skills/datahub-skills.md
/datahub-skillsUse Cases
Usage Examples
/datahub-skills plan-connector source=postgres target=snowflake
/datahub-skills search-catalog query=customer_360 domain=marketing
/datahub-skills trace-lineage urn=urn:li:dataset:(urn:li:dataPlatform:snowflake,my_db.my_schema.my_table,PROD)
Security Audits
Frequently Asked Questions
What is datahub-skills?
This skill provides a comprehensive toolkit for interacting with DataHub, enabling developers to plan connectors, review PRs, search the catalog, enrich metadata, trace lineage, manage data quality, and set up connections. It streamlines data discovery and governance tasks directly within Claude Code.
How to install datahub-skills?
To install datahub-skills: create the skills directory (mkdir -p .claude/skills), then add the config to .claude/skills/datahub-skills.md. Finally, /datahub-skills in Claude Code.
What is datahub-skills best for?
datahub-skills is a skill categorized under Data & Analytics. It is designed for: code-review. Created by DataHub.
What can I use datahub-skills for?
datahub-skills is useful for: Plan a new data connector by specifying source and target systems and reviewing recommended configurations.; Review a pull request for a DataHub ingestion recipe, checking for schema mapping and metadata compliance.; Search the DataHub catalog for datasets related to a specific business domain and retrieve their lineage.; Enrich metadata for a dataset by adding descriptions, tags, and ownership information via the DataHub API.; Trace end-to-end lineage for a critical data asset to understand upstream dependencies and downstream impact.; Set up a new DataHub connection by providing connection details and testing connectivity..