Data engineering & analytics

Build dashboards that answer business questions

Power BI/Tableau/Looker Studio: model data, KPIs, drill-downs, publish and present.

~20 focused hours·beginner

Tools: Power BI, Tableau, Looker Studio, DAX, SQL

Market relevance — share of job ads asking for this
What employers mean

You should be able to…

  1. Model a star schema (fact + dimension tables) from raw exports before building visuals
  2. Write basic-to-intermediate DAX or calculated fields for KPIs (YoY growth, running totals)
  3. Build drill-down dashboards a non-technical stakeholder can self-serve
  4. Connect live data sources (database, Google Sheets, API) rather than static file uploads
  5. Design for the audience: pick the right chart type, avoid clutter, highlight the one number that matters
  6. Publish and share a dashboard with proper access/refresh scheduling
  7. Present a dashboard live and answer 'why' questions the visuals alone don't explain

Needs first: Query and model data with SQL

Learn — free, link-checked

The few resources that matter

Practice

Power BI dashboard for a Tier-2/3 India kirana-delivery business

Simulate 6 months of order data for a hyperlocal delivery business (order time, city, delivery partner, UPI vs COD, delay minutes, rating) and build a Power BI or Looker Studio dashboard with a KPI summary page and two drill-down pages (by city, by delivery partner). Model the data properly with a star schema rather than one flat table.

Done when
  • Data is modeled as fact + dimension tables, not one wide flat sheet
  • At least 3 DAX/calculated measures beyond simple SUM (e.g. % on-time, MoM growth, repeat-customer rate)
  • Drill-down works: clicking a city on the summary page filters the detail page
  • Published/shareable link or a 3-5 min recorded walkthrough explaining design choices
Prove it

Evidence a recruiter can check

  • Published Power BI/Tableau Public/Looker Studio dashboard link that a recruiter can open and interact with
  • Public GitHub repo with the data model documentation and DAX/calc-field formulas explained
  • A short recorded walkthrough (Loom) presenting the dashboard as if to a business stakeholder
  • Microsoft Learn Power BI learning-path completion badge, linked
Interview

Questions you'll get asked

  1. Walk me through how you'd design a dashboard for a sales team from scratch — what do you ask first?
  2. What's the difference between a calculated column and a measure in Power BI/DAX?
  3. How do you handle a dashboard that's slow because the underlying data model is a mess?
  4. When would you use a line chart vs. a bar chart vs. a table — and when should you NOT use a pie chart?
  5. How do you set up row-level security so different regional managers see only their data?
  6. A stakeholder asks for '20 more metrics' on one page — how do you push back constructively?
  7. How would you set up scheduled refresh for a dashboard fed by a live SQL database?
See where you stand for AI-enabled Data Analyst