This repository captures a full learning journey in Excel, starting from core visualization practice and evolving into strategic decision dashboards, forecasting, and simulation-backed business planning.
The project was built week by week, and each week added a new layer of maturity:
- Visual design and interactivity
- Multi-perspective business reporting
- Strategy design with Goal Seek
- Forecasting and risk simulation
- Final integrated submission
| Week | Focus | Main Output | Workbook(s) | Video |
|---|---|---|---|---|
| Week 0 | Incubator fundamentals | Basic and advanced interactive visuals | Week0_macros.xltm | ALPHAA AI Week 0 INCUBATOR'S WEEK |
| Week 1 | US Superstore analysis | Three-perspective dashboard system | Week1_Alphaa Superstore Nov 2020.xlsm | ALPHAA AI Week 1 Task |
| Week 2 | Promotion strategy | 25% growth plan, two versions | Week3_1.xlsm | Week 2 Task, Week 2 Task Version 2 |
| Week 3 | Forecasting and simulation | Monte Carlo feasibility and bounded forecasts | Week3_1.xlsm | Week 3 (Forecast and Monte Carlo) |
| Week 5 | Final consolidation | Final end-to-end dashboard submission | WEEK-5_Sharable.xlsm, Superstore-Retail-Sep-2020_2_new.xlsm | WEEK 5 ( Final Week Submission ) |
What we did:
- Built basic and advanced Excel visualizations to establish dashboard fundamentals.
- Created an advanced view for top IPL batsmen (Chris Gayle, David Warner, Virat Kohli) across 2008 to 2016.
Extra challenge we incorporated:
- Implemented interactive player filtering so clicking a player updates the career stats view dynamically.
- Tackled the challenge of making visual outputs feel real-time and responsive.
Why it mattered:
- This week established interaction design habits used in later business dashboards.
Links:
- Workbook: Week0_macros.xltm
- Video: ALPHAA AI Week 0 INCUBATOR'S WEEK
What we did:
- Built a large-scale dashboard using about 10,000 Superstore records (2016 to 2019).
- Structured the solution into three business views:
- Store Owner view for KPI tracking (revenue, profit, trend, satisfaction).
- Data Analyst view for relationship analysis (discount impact on sales/profit).
- Fact-Based view for top-5 entities (categories, customers, states, products).
Extra challenge we incorporated:
- Added slicers to compare year and quarter performance quickly.
- Included delivery status and customer satisfaction for a more complete business-health view.
Why it mattered:
- One dataset was transformed into role-based decision dashboards, not just one generic report.
Links:
- Workbook: Week1_Alphaa Superstore Nov 2020.xlsm
- Video: ALPHAA AI Week 1 Task
What we did:
- Designed a regional promotion strategy to achieve 25% overall sales growth.
- Created two variants: one insight-heavy and one optimized for creativity and automation.
Extra challenge we incorporated:
- Used Goal Seek to quantify the quantity and pricing milestones required to hit the target.
- Used average year-over-year growth to identify high-potential products (for example, Copiers in West with strong growth behavior).
- Identified opportunity zones by spotting cities below regional average sales.
Why it mattered:
- The dashboard evolved from descriptive analytics to prescriptive planning.
Links:
- Workbook: Week3_1.xlsm
- Video: ALPHAA AI Week 2 Task
- Video: Alphaa AI Week 2 Task Version 2
What we did:
- Evaluated whether the Week 2 strategy was actually feasible.
- Built a forecasting layer with statistical confidence framing.
Extra challenge we incorporated:
- Ran 1,000 Monte Carlo simulations to estimate probability of achieving the 25% goal.
- Moved beyond straight-line projection by including seasonal behavior, especially Q4 uplift.
- Broke down annual target into monthly and quarterly checkpoints.
- Added upper and lower prediction bounds for risk-aware planning.
Why it mattered:
- Strategy decisions became probability-aware rather than assumption-driven.
Links:
- Workbook: Week3_1.xlsm
- Video: Alphaa AI Week 3 (Forecast and Monte Carlo)
What we did:
- Finalized a complete dashboard system that integrated strategy, forecasting, and simulation outputs.
- Converted all weekly learnings into one coherent, presentation-ready final outcome.
Why it mattered:
- This week demonstrated end-to-end business decision support with Excel.
Links:
- Workbook: WEEK-5_Sharable.xlsm
- Workbook: Superstore-Retail-Sep-2020_2_new.xlsm
- Video: WEEK 5 ( Final Week Submission )
- Full playlist: Alphaa AI | Ft. Tirth Shah
- My Video Resume for Alphaa AI
- Marketing Challenge Dashboard (Excel) (Ft. Tirth Shah)
- LinkedIn Profile Analysis
- New year challenge dashboard
- Open the workbook for the week you want to inspect.
- Explore data sheets first, then calculation sheets, then dashboard sheets.
- Use slicers and interactive controls to reproduce insights.
- Compare workbook behavior with the matching week video.
Tirth Shah