Stage 1: Foundations
- Comfortable with Excel: formulas, pivot tables, basic charts
- Basic understanding of what data types mean (text, number, date) and why they matter
- Simple statistics: mean, median, percentages, trends
Stage 2: Core Tools
- SQL — SELECT, WHERE, GROUP BY, JOIN. This is how you pull data from real company databases.
- Power BI — Power Query for cleaning, data modeling, DAX basics, and dashboard building
- Optionally: basic Python or R, useful but not required for most analyst roles
Stage 3: Applied Skills
- Build 2–3 complete portfolio projects using real or realistic datasets
- Practice explaining findings in plain language, not just technical terms
- Learn to ask good questions of data before jumping into building — what decision will this analysis inform?
Stage 4: Job Ready
- A portfolio (even informal — a folder of dashboards with short write-ups) you can walk someone through
- Comfortable answering both technical and scenario-based interview questions
- A resume that highlights specific outcomes, not just tool names
Suggested Timeline
Weeks 1-2
Foundations
Weeks 3-6
Core Tools
Weeks 7-10
Projects + Job Prep
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This is a realistic pace for consistent part-time learning (5–8 hours/week). Going faster is possible, but the projects stage is where the pace naturally slows down — and that's fine, it's the most valuable part.