Check a dataset before analysis
Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
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Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
Match a chart to the question, data types, and comparison people need to make.
Understand a formula’s inputs, intermediate steps, assumptions, and possible failure cases.
Check a query’s joins, aggregation, null handling, and expected row counts.
Write a concise performance narrative that separates changes, explanations, and next steps.
Define a measurable hypothesis, comparison, and decision rule before collecting results.
Inspect dataset structure, missingness, duplication, and validity before analysis.
Review SQL grain, joins, aggregation, and null handling with concrete examples.
Analyze a supplied CSV with explicit assumptions and reproducible summaries.
Translate a hypothesis into an interpretable test with metrics and guardrails.
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