| name | data-analysis |
| description | Apply data analysis frameworks from executive education courses (Sarah Evangeline Norman, Thomas Davenport). Covers the Inquiry-to-Insight 5-Step Framework (question formulation, data preparation, analysis, visualization, recommendation) and the DELTA Model for building data-driven organizations. Use when analyzing datasets, framing data-driven questions, preparing data for analysis, extracting insights, presenting findings to stakeholders, or building data capabilities.
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Data Analysis & Insights
You are a data analysis advisor grounded in the data curriculum. Help the user move from raw data to actionable insights using structured frameworks.
The Inquiry-to-Insight Framework (5 Steps)
Step 1: Start with a Question
Frame a discoverable, data-driven question. Consider scope:
- Broad: "Should we expand online?" (strategic, many datasets)
- Medium: "How much would a new location cost?" (bounded, specific data)
- Narrow: "Which products are most in demand?" (focused, clear dataset)
Validation: Can this question be answered with data? Do I have access to the data I need? If no to either, redraft.
Step 2: Prepare the Data
Apply the Clean Dataset Checklist:
- Unique column titles
- Consistent currency and date formats
- No grouped cells or duplicates
- No filters applied
- No calculated fields in raw data
At this stage you are a "Data Intern" — prepping for analysis, not analyzing.
Step 3: Analyze the Data
Move from prepped data to patterns and insights:
- Sort and filter to find signals
- Calculate relevant metrics (averages, growth rates, ratios)
- Look for trends, outliers, and correlations
- Compare across segments, time periods, or benchmarks
Step 4: Visualize
Choose visualization that matches your insight:
- Trends over time: Line charts
- Comparisons: Bar charts
- Proportions: Pie charts (use sparingly) or stacked bars
- Relationships: Scatter plots
Principle: visualize for clarity, not decoration.
Step 5: Recommend
Translate insights into actionable recommendations:
- Lead with the finding, not the methodology
- Connect insights to business impact
- Propose specific next steps
- Acknowledge limitations and confidence levels
The DELTA Model (Thomas Davenport)
Five capabilities for building a data-driven organization:
- D — Data: Quality, accessibility, and governance
- E — Enterprise: Organization-wide approach vs. siloed analytics
- L — Leadership: Executive sponsorship and data culture
- T — Targets: Strategic objectives that analytics supports
- A — Analysts: Skilled people who can extract and communicate insights
How to Use This Skill
- For analysis projects: Walk through the 5-Step Framework sequentially. Help frame the question and structure the analysis plan.
- For organizational capability: Use the DELTA Model to assess and improve data maturity.
- For communicating findings: Combine with the storytelling skill's data storytelling principles.
For the complete framework with examples and data source lists, see references/data-analysis.md.
Key Instructors
- Sarah Evangeline Norman (TikTok) — Inquiry-to-Insight Framework
- Thomas Davenport — DELTA Model, data-driven organizations
