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Data prompts

Data prompts for cleaning, interpreting, and explaining numbers to non-technical readers. 31 prompts in this category, 0 readable for free.

• Write SQL and state the metric definitions Locked

  Write SQL for me. Requirement: {{business need}}; schema: {{tables and fields}}; dialect: {{database}}. Requir

• Attribute a metric shift Locked

  The metric {{metric}} moved from {{before}} to {{after}}, a change of {{magnitude}}. Attribute it structurally

• Design an A/B test Locked

  I want to test {{hypothesis}}. Context: {{context}}; baseline: {{baseline}}. Design it: (1) one primary succes

• Interpret A/B results without fooling yourself Locked

  Here are my experiment results: {{results}}. Interpret rigorously and check each: (1) statistical significance

• Define a north-star metric with guardrails Locked

  My business is {{business}} and the current stage goal is {{goal}}. Design the metric system: (1) propose thre

• Funnel analysis to locate drop-off Locked

  Here is my product's funnel data: {{funnel}}. Analyze: (1) compute step conversion and drop-off, then name bot

• How to read a retention curve Locked

  Here is my retention data: {{retention}}. Read it: (1) does the curve flatten, and at what level — no plateau

• Segment comparison and Simpson's paradox Locked

  I observe {{aggregate finding}} overall, but {{segmented finding}} by segment — they conflict. Determine: (1)

• Choose and design the right chart Locked

  I need to show {{data}} to {{audience}}, and I want them to conclude {{conclusion}}. Advise: (1) the best char

• Metric definition alignment doc Locked

  Our team disagrees on how to define {{metric}}. Version A: {{A}}; version B: {{B}}. Produce an alignment docum

• Turn a business question into a data request Locked

  A stakeholder asked: '{{question}}'. Turn it into an executable data request: (1) clarify the actual decision

• Data quality checklist Locked

  I will use this dataset for {{purpose}}. Source: {{source}}. Give me a prioritized quality checklist: (1) comp

• Express a forecast honestly Locked

  I need to forecast {{metric}} for the next {{period}} based on {{data}}. Provide: (1) a point estimate plus a

• Correlation is not causation Locked

  I found a correlation between {{A}} and {{B}} (data: {{data}}). Analyze rigorously: (1) enumerate every possib

• Explain data findings to non-technical stakeholders Locked

  I need to present this analysis to {{audience}}: {{findings}}. They do not know statistics and only care wheth

• Generate an Excel formula Locked

  You are an Excel expert. Generate a formula: (1) the formula with a part-by-part explanation; (2) use case and

• Plan data-cleaning steps Locked

  You are a data engineer. Design cleaning steps for this data: (1) list likely issues (missing, duplicate, form

• Tell a story with data and charts Locked

  You are a data-storytelling expert. Turn the data into a story: (1) a one-line conclusion first; (2) structure

• Design a metrics framework Locked

  You are an analytics expert. Design a metrics framework: (1) set the north-star metric and goal; (2) split int

• Handle missing values and outliers Locked

  You are a data-science expert. Handle missing values and outliers: (1) judge if missingness is random or syste

• Structure a data-analysis report Locked

  You are a data analyst. Structure the report: (1) lead with conclusions (findings and recommendations in 3 lin

• Design analytics tracking Locked

  You are a data-product expert. Design tracking: (1) derive events and properties from the analysis goal; (2) n

• Write a data dictionary Locked

  You are a data-governance expert. Write a data dictionary: (1) name, meaning, type and values per field; (2) d

• Analyze a time series Locked

  You are a time-series expert. Analyze the data: (1) decompose trend, seasonality and residual; (2) spot anomal

• Detect anomalies Locked

  You are an analytics expert. Detect anomalies: (1) define what counts as anomalous; (2) choose statistical or

• Do a pivot-table analysis Locked

  You are an analytics expert. Design a pivot analysis: (1) the business question; (2) row, column and value fie

• Design a dashboard Locked

  You are a data-product expert. Design a dashboard: (1) audience and purpose; (2) core metrics and chart types;

• Extract and transform data Locked

  You are a data engineer. Design an ETL flow: (1) source and target format; (2) extract, clean and transform st

• Choose a correlation analysis method Locked

  You are an analytics expert. Choose a correlation method: (1) Pearson, Spearman or chi-square by data type; (2

• Design sampling and avoid bias Locked

  You are a statistics expert. Design sampling: (1) choose random, stratified or systematic; (2) compute sample

• Analyze text data Locked

  You are a text-analysis expert. Analyze text data: (1) the goal (topic, sentiment, classification); (2) suitab

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