DataHub

Use DataHub’s search functionality to discover datasets based on keywords, tags, and descriptions.

Review data lineage to understand the origin and transformations of the data.

Check data quality assertions to ensure data accuracy and completeness.

Access data samples and documentation to assess the suitability of the data for the AI/ML project.

Use DataHub to identify and tag PII within datasets.

Define data ownership and access controls.

Monitor data usage and track compliance metrics.

Generate reports for auditing and compliance purposes.

Use DataHub’s data lineage feature to trace data flow and identify potential bottlenecks.

Review data quality checks and error logs to pinpoint the source of the problem.

Collaborate with data owners to understand the impact of the issue and implement a fix.

Monitor the pipeline to ensure the issue is resolved and data quality is restored.

Use DataHub to create a comprehensive data catalog with clear descriptions and documentation.

Define data access policies and grant permissions to business users.

Provide training and support to help users navigate the data catalog and access the data they need.

Monitor data usage and gather feedback to improve the self-service data access experience.

Use DataHub to define and implement data quality checks and assertions.

Monitor data quality metrics and track trends over time.

Identify and address the root causes of data quality issues.

Implement data quality improvement initiatives and measure their impact.