Skills
Tools in service of the question.
I care less about tool worship and more about the right tool for the question in front of me. Here's the working stack and what each piece actually does in my day-to-day.
SQL
92%- JOINs (INNER, LEFT, FULL)
- Subqueries & CTEs
- CASE statements
- Aggregations & window basics
- SSMS / T-SQL
Power BI
88%- Report & dashboard design
- DAX measures
- Drill-throughs & bookmarks
- Visual hierarchy for executives
Excel
90%- Pivot tables & power pivots
- INDEX/MATCH, XLOOKUP
- Conditional logic & lookups
- Reporting templates
Data Cleaning
88%- Power Query M
- Deduplication & normalization
- Type coercion & null handling
- Source reconciliation
Python
70%- Pandas wrangling
- Matplotlib / Seaborn
- Notebook-first analysis
- Light scripting & automation
Dashboard Design
85%- Information hierarchy
- Color & contrast for clarity
- Accessibility-aware visuals
- Narrative-led layouts
Prompt Engineering
78%- Structured prompting
- Few-shot framing
- Behavioral guardrails
- LLM-assisted analysis
Statistical / ML Foundations
65%- Descriptive & inferential basics
- Correlation vs. causation
- Regression intuition
- Clustering fundamentals