Using The “DIG” Framework for Data Analysis

Step 1: Description Goal: Understand a new dataset from scratch and surface data quality issues early. Scenario: You're given a spreadsheet with zero context. Prompt 1: Dataset Overview "List all the columns in the attached spreadsheet and show me a sample of data from each column." Prompt 2: Sanity Check "Take 5 random samples from each column to confirm the format and type of information." Prompt 3: Data Quality Check "Run a data quality check on each column. Look for missing values, unexpected formats, and outliers." Key Insight: * Reveals what the data can and cannot be used for. * Prevents wrong analysis due to broken or incomplete data. Step 2: Introspection Goal: Verify that ChatGPT/Gemini/CoPilot truly understands the data and explore meaningful questions. Prompt 1: Insight Brainstorming "Suggest 10 interesting questions we could answer with this dataset and explain why each matters." Prompt 2: Feasibility Check "For the first 3…