Data practice assessment. Applied

Practice assessment: short scenarios that test judgement and help you write defensible CPD reflections. Not timed.

12 questions

Scenario: A schema change breaks downstream reports. What reduces blast radius?

evolution

Scenario: Pipelines run but outputs degrade silently. What do you add?

monitoring

Scenario: You must choose quality checks. What makes a check 'good'?

quality

Scenario: You need to prove lineage for an audit. What evidence do you keep?

lineage

Scenario: Teams keep rebuilding the same transformations. What is the best architectural response?

operating-model

Scenario: You need to backfill historical data after a bug. What is the main risk?

evolution

A freshness SLO for a dataset is most defensibly defined as:

monitoring

Scenario: A check fails. What makes the response credible?

quality

Scenario: A dataset is correct but arrives too late for decisions. What should you add?

monitoring

Scenario: A column is renamed and downstream breaks. What design practice prevents this?

evolution

Scenario: A privacy incident occurs. What helps you scope impact quickly?

lineage

Scenario: Central team is overloaded. What is the most defensible scaling move?

operating-model

Add CPD reflection (optional)

One short paragraph makes your CPD evidence much stronger.

Pick one question you got wrong. Write a small “prevention plan”: what check, owner, and alert would stop that failure reaching a dashboard.

Quick feedback