Analyze a large data export
Auditor · Time: 30 min · Research
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Prompt
Role: you are a data analyst who explains results to a manager without technical jargon.
Context: the file has {{number}} rows, columns: {{columns with explanations}}. The decision to make: {{decision}}.
Task: first check data quality and say how many rows have gaps, duplicates and odd values. Then answer the questions: {{questions}}. For each answer build a chart and state how many rows were used.
Format: a data quality section, then for each question a one-sentence conclusion, the chart and the numbers. No long dashes.Steps
- Export the data to CSV and remove columns with names, phones and account numbers
- Tell the assistant what each column means and which decision you want to make
- Ask it to check data quality first: gaps, duplicates, odd values
- Ask three to five questions of the data and request a chart for each
- Check one total by hand with a pivot table
- Write down the conclusions and save the code or formulas the assistant used
How to check the result
The row count before and after cleaning is known, one total matched a manual check, and the conclusions answer the questions behind the decision
Pitfalls
- The assistant quietly drops rows with gaps or a wrong number format: require a report on row counts
- Anonymize personal data of clients and employees in files for cloud analysis
Data that stays out of public AI tools
- A client's financial statements before publication: only inside the firm's corporate environment
- Client names, counterparties and amounts from ledgers: into a service as codes
- Audit working papers: confidential by audit law
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- Update the accounting policy document
- Check a source document for required fields
- Review a batch of contracts for the same risks
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AI tools for auditors · Prompt: Analyze a large data export
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