Practitioner
Contribute and maintain metadata
For the people accountable for data assets: adding and maintaining metadata, tests and contracts.
What you will be able to do
- Enrich and maintain metadata at scale using automations rather than manual edits
- Apply classification and sensitivity tags consistently across domains
- Build scoped, scheduled automations that maintain metadata without manual edits
- Improve the discoverability of the assets you own
- Build and monitor data quality tests that catch issues before consumers do
- Package related assets into data products with clear ownership
- Design governance workflows that match how your organization approves things
- Write a data contract that turns a consumer assumption into an enforceable term
How this track works
- Complete Foundations first
- Work through the eight Practitioner modules
- Pass the knowledge check
Modules
Data Governance Basics
Applying classification at scale using automations and filters rather than tagging by hand.
10 minAI Automations
The general machinery for changing metadata at scale: scope, conditions, actions and cadence, including AI generated descriptions.
15 minData Products
Packaging related assets into something with a name, an owner and a consumer.
10 minReverse Metadata
Writing curated metadata back into the source system so context travels with the data.
10 minObservability and Profiling
Measuring the shape of data over time, and sampling sensibly at scale.
10 minCustom Metrics and Alerts
Expressing a business specific quality rule in SQL and routing it to someone who can act.
10 minCustom Governance Workflow Builder
Building approval and review processes visually, so governance matches how your organization actually works.
10 minData Contracts
Writing the explicit agreement between the people who produce data and the people who depend on it.
10 minPractitioner knowledge check
10 questions, 8 to pass, unlimited retakes. Every answer is explained.