Data practice assessment. Foundations

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

12 questions

Scenario: Two teams argue because customer_id means different things. What prevents this best?

contracts

Scenario: Missing values are treated as zero. What failure can this create?

quality

Scenario: A field is an identifier but is used numerically in a model. Why is that risky?

modelling

Scenario: A metric improves after a pipeline change, but trust drops. What should you check first?

metrics

Scenario: A dashboard looks great but decisions are wrong. What data risk is most likely?

aggregation

Scenario: Null and empty string are treated as the same. Why is this risky?

quality

Scenario: A dataset contains names and emails. What should happen first?

privacy

A data contract should include:

contracts

Scenario: A KPI changed unexpectedly. What is the fastest way to narrow the cause?

lineage

Scenario: A dataset is used for decisions but has no owner. What is the risk?

quality

Scenario: A metric is used for bonuses. What should you do first to keep it credible?

metrics

Scenario: Analysts want access to a sensitive dataset. What is the most defensible default?

privacy

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.

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