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No “Titanic” Datasets Allowed.

Real-world business scenarios that force you to use Advanced SQL and build actual Dashboards.

How to do these projects for free:

  1. Download the CSV from Kaggle.
  2. Upload it to Google BigQuery Sandbox (Free, no install needed).
  3. Write your SQL queries there.
  4. Connect Power BI Desktop or Tableau Public to BigQuery.
E-CommercePower BI

Customer Segmentation & Revenue Performance Dashboard

The Business Ask:

“Hi Analyst, The Head of E-Commerce is concerned we're treating all 4,300+ customers the same. She wants to see segments (Champions vs At-Risk) to optimize the upcoming 20% off promotion. specifically: Revenue contribution by segment and Month-over-month trends.”

SQL CONCEPTS REQUIRED:

  • Window Functions (NTILE, ROW_NUMBER)
  • CTEs (Common Table Expressions)
  • CASE Statements
  • Date Functions (DATEDIFF)
  • Self-Joins
Strategy: Load CSV to BigQuery > Write SQL for RFM Scoring > Visualize segments in Power BI.
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MarketingTableau

Campaign ROI & Conversion Funnel Analysis

The Business Ask:

“The CMO wants to know why our 'Summer Sale' campaign had high clicks but low purchases. Analyze the click-stream data to find the exact drop-off point in the funnel and calculate CAC (Cost Acquisition Cost) per channel.”

SQL CONCEPTS REQUIRED:

  • Left Joins vs Inner Joins
  • Aggregations (SUM, COUNT)
  • Conversion Rate Calc
  • COALESCE
Strategy: Clean data in SQL > Calculate step-by-step conversion rates > Build Funnel Viz.
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Supply ChainPower BI

Supply Chain Delivery Risk & Late Shipment Analysis

The Business Ask:

“Hi Analyst, Our on-time delivery rate dropped to 59% last quarter, and customer complaints are up 40%. The Logistics Team blames the carriers, but I suspect internal processing bottlenecks. I need a 'Source of Truth' dashboard for next week's Ops Review that reveals: - Real vs. Scheduled shipping variance by Region. - Breakdown of 'Late Delivery Risk' by Shipping Mode. - Root Cause: Is it Order Processing delay or Shipping delay? - James, SVP Operations”

SQL CONCEPTS REQUIRED:

  • Date Functions (DATEDIFF, DATE_TRUNC)
  • Window Functions (AVG, SUM OVER)
  • CTEs (Common Table Expressions)
  • CASE Statements (Delay Bucketing)
  • Correlated Subqueries
Strategy: Calculate Shipping Variance (Real vs Scheduled) > Create 'Delay Buckets' (1-3 days, 3+ days) using CASE > Aggregate On-Time Rate by Region > Visualize in Power BI.
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Financial AnalyticsTableau

Corporate P&L & Budget Variance Analysis

The Business Ask:

“Hi Analyst, The CFO is tired of opening 14 Excel files for the monthly close. He needs a self-service P&L dashboard for the Board Meeting in 2 weeks. Requirements: - Budget vs. Actuals by Cost Center and GL Account. - Year-over-Year variance (FY23 vs. FY22). - Auto-flag line items with >10% unfavorable variance. This is high visibility. Triple-check the numbers before publishing. - Controller”

SQL CONCEPTS REQUIRED:

  • Pivot / Unpivot Logic
  • Window Functions (LAG for YoY)
  • GROUP BY ROLLUP (Hierarchies)
  • CASE Statements (Variance Flags)
  • CTEs (Budget vs. Actuals)
Strategy: Unpivot monthly GL data > Calculate $ and % Variance via CTEs > Use LAG for YoY comparisons > Implement 'Red Flag' logic for >10% variance > Build P&L Waterfall & Heatmap in Tableau.
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HR / People OpsTableau

Employee Attrition Risk Dashboard

The Business Ask:

“Our retention rate dropped to 85%. The CHRO wants to know: Is it salary? Or is it manager rating? Build a report correlating 'Years at Company' vs 'Last Pay Raise'.”

SQL CONCEPTS REQUIRED:

  • Subqueries
  • AVG / MEDIAN logic
  • Correlation analysis (via SQL)
  • String Manipulation
Strategy: Join Employee & Performance tables > Calculate Retention Rates > Visualize correlation in Tableau.
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HealthcareTableau

Patient Readmission Risk & Clinical Quality Dashboard

The Business Ask:

“Hi Analyst, CMS just sent another warning. Our 30-day readmission rate for diabetic patients is 19.4% (National Benchmark: 15.7%), putting us at risk of $3.2M in Medicare penalties. The CMO needs a descriptive analysis dashboard to identify specific drivers: - Which demographics (Age, Race) have the highest failure rates? - Do more lab procedures correlate with lower readmission? - Is 'Time in Hospital' a valid predictor? We need to identify the 'High Risk' segments immediately to design better discharge protocols. - Director of Quality Improvement”

SQL CONCEPTS REQUIRED:

  • Window Functions (COUNT OVER)
  • CTEs (Cohort Segmentation)
  • CASE Statements (Risk Flagging)
  • Complex Aggregations (Clinical Factors)
  • HAVING Clauses (High-Risk Filtering)
Strategy: Clean data (exclude Hospice/Expired) > Create 'Readmission Risk' flags (<30 days) via CASE > Aggregate Readmission Rates by Demographics & Clinical Factors > Compare vs 15.7% Benchmark > Visualize High-Risk Cohorts in Tableau.
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Product AnalyticsTableau

Product Growth: DAU/MAU Stickiness & Feature Adoption

The Business Ask:

“Hi Analyst, The Executive Product Review is next Wednesday. I need a 'Pulse' dashboard on our engagement health. Key questions for the deck: - Are we actually growing? (DAU/MAU trends & Stickiness Ratio). - Which features are dead weight? (Identify <5% adoption). - How does retention look by cohort? (Week 1 vs Week 12). No complex models, just clean descriptive analytics sliced by User Segment (Age, Tier). - VP of Product”

SQL CONCEPTS REQUIRED:

  • Self-Joins (Cohort Retention)
  • Window Functions (DAU/MAU)
  • LAG (Week-over-Week Growth)
  • Date Functions (DATE_TRUNC)
  • Complex Aggregations
Strategy: Calculate DAU/MAU & Stickiness via Window Functions > Measure Feature Adoption Rates > Build Cohort Retention Heatmap using Self-Joins > Calculate Session Metrics > Visualize Growth Trends in Tableau.
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