1. Advanced Excel: Pivot tables, VLOOKUP/XLOOKUP, index-match, and conditional modeling. 2. SQL Mastery: Aggregations, window functions, CTEs, and cohort retention queries. 3. BI Dashboards: Interactive visual storytelling in PowerBI or Tableau. 4. Python/R Automation: Automating data extraction, cleaning, and scheduled reporting.
Identify your exact skill gaps and follow a milestone-by-milestone curriculum tailored to your target engineering track.
Yes! Data Analysts build strong SQL intuition and commercial domain knowledge, making it a natural launching pad toward Data Science.
Continue leveling up your technical and job search skills.
From inner/outer joins and GROUP BY filtering to window functions (ROW_NUMBER, DENSE_RANK) and database indexing mechanics.
Statistical inference, hypothesis testing, A/B experiment design, predictive modeling, and executive storytelling through data visualization.
A practical roadmap for professionals transitioning from mechanical, civil, operations, or non-tech backgrounds into software development.