Lesson 16 / 25

Data quality

Apply Data quality with clear evidence.

Understand Data quality

For Data quality, begin with the problem it solves. Identify the inputs, constraints, and observable outcome before choosing an implementation.

See the workflow

Use this path while practising Data quality: understand, act, verify, and improve.

Workflow for Data quality.
Figure 4.1 — A repeatable workflow.

A useful comparison

Data quality is like a route plan: it keeps each step connected to a destination.

Check your reasoning.

Quick check: What is the best first step for Data quality?

  • Define the goal and constraints.
  • Copy an unverified example.
  • Skip measurement.
Answer

Define the goal and constraints. — A clear goal and constraints make decisions reviewable.