Data Science · Advanced level

Advanced level · Module 5: Data Governance and Responsible Data Science · Lesson 1 of 4

Data Governance and Quality

Define who is responsible for data and measure and improve its quality.

In this lesson you will

  • Describe data governance roles
  • Assess data against quality dimensions

Key concepts

data owner and stewardquality dimensionsquality checksissue log

The lesson

Data governance assigns responsibility: data owners decide how data may be used, stewards maintain quality and definitions, and analysts use data within agreed rules.

Quality has several dimensions: completeness, accuracy, consistency, timeliness and validity. Measure them with automated checks rather than impressions.

Log quality issues with owners and deadlines so they are fixed at the source, not repeatedly patched in each analysis.

Step by step

  1. Identify owners and stewards for the project's data sets.
  2. Write automated quality checks for each dimension.
  3. Run them and log issues.
  4. Agree fixes with owners.

Practice activity

Write a data quality report for the provided project.

Expected result: A report with measured quality and an issue log with owners.

Check your understanding

  1. Name three data quality dimensions.

    Show answer

    For example completeness, accuracy and timeliness.

  2. Why fix issues at the source?

    Show answer

    So every later use benefits, instead of patching each analysis.

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