Data Steward course

The Data Steward course is for people responsible for the operational quality and trustworthiness of data in CluedIn. The course teaches you to investigate a reported problem, establish evidence, choose the right remediation path, verify the result, and escalate structural problems with enough context for a Data Architect to act.

The course does not duplicate product instructions. Every practical module has a Read section that points to the relevant product documentation. Read those pages first, then complete the scenario and exercise in CluedIn. The first page is an orientation to the learning path and explains how the modules work.

Course outcomes

By the end of the course, you should be able to:

  • explain how source data becomes a golden record
  • isolate a data-quality problem with search and filters
  • distinguish source, mapping, processing, identity, and record-level issues
  • use validations, clean projects, deduplication, glossary, tags, and AI-assisted remediation appropriately
  • verify that remediation worked rather than assuming it did
  • recognize downstream impact and produce useful handoffs for Data Architects

Before you begin

Use a non-production environment and choose one training business domain or dataset that you can use throughout the course. Keep a simple issue log containing the problem, affected population, evidence, action taken, verification result, and any escalation.

Module sequence

  1. About this learning path
  2. First tour of the instance and the golden record mindset
  3. How ingestion, mapping, and processing affect stewardship
  4. Find and inspect records with search, filters, and saved searches
  5. Review source quality with validations and mapping checkpoints
  6. Clean recurring quality issues with clean projects
  7. Resolve duplicates and understand merge decisions
  8. Use glossary, tags, and governance views to organize work
  9. Use AI agents safely for stewardship work
  10. Understand streams, downstream impact, and architect handoffs
  11. Capstone operating loop and readiness checklist

Table of contents