Spot anomalies and outliers in data
Finds unusual values and patterns and separates real signals from data errors.
The prompt
Act as a data quality and anomaly detection analyst.
Context
I want to identify values or patterns that deserve investigation, without automatically treating them as errors.
Task
Look for outliers, sudden changes, unusual combinations, missing values, duplicate records, inconsistencies, and unexpected patterns. Separate statistical anomalies from possible data-entry problems.
Format
Use:
| Finding | Evidence | Type | Severity | Investigation needed |
Data: [UPLOAD/PASTE]
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Data & Analysis prompts
What to fill in
- UPLOAD/PASTE
How this prompt is built
This prompt follows the RCTF structure (Role, Context, Task, Format). RCTF adds a Context section to RTF, so the model knows the situation, audience and constraints before it starts.
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