Selbstgesteuertes Projekt
Business Analytics Sprint
Data Science · August 2026
Eine ProoV-Fallstudie · Lernprojekt, kein Arbeitsverhältnis
Built an end-to-end profitability investigation that framed the problem with hypotheses and a KPI driver map, audited the data for issues, and wrote correct SQL to calculate category margins. The analysis connected margin erosion to pricing, input-cost, and logistics pressures, then turned those findings into a quantified recovery forecast, prioritized recommendations, and a concise boardroom narrative.
Bewertet nach
- Problem Framing & Hypotheses10%
- Data Analysis & SQL30%
- Root-Cause & Forecasting25%
- Dashboard & Visualization15%
- Executive Communication & Strategy20%
Bestanden · Bestehensgrenze 60/100
Was herausstach6
- Identified the core paradox with concrete numbers: revenue up 17% while profit fell 55%, and margin dropped from 13.4% to 5.2%.
- Built a correct category-profit SQL query using SUM(revenue), SUM(cost), and the proper margin formula.
- Produced a credible recovery scenario with named levers and quantified impact, including logistics, raw-material hedging, and discount discipline.
- Prioritized recommendations with effort/impact logic and translated the analysis into boardroom-ready headlines.
- Structured Hypothesis Formation
- Leakage-Free KPI and Data Audit Thinking
Meine eingereichte Arbeit18 Aufgaben
10 Aufgaben · 4.2k Zeichen · 8 Textantworten · 229 Wörter
- Hypothesis Sheet690 Zeichen
- KPI Driver Map174 Zeichen
- Data Audit100 Zeichen
- Week1 Update476 Zeichen
- Sql Category Profit318 Zeichen
- Dashboard58 Zeichen
- Forecast280 Zeichen
- Recommendations694 Zeichen
- Boardroom Deck578 Zeichen
- Bosch Real Case Study834 Zeichen
- Hypothesis Sheet76 Wörter
- KPI Driver Map1 Wort
- Data Audit4 Wörter
- Week1 Update63 Wörter
- Sql Category Profit24 Wörter
- Dashboard1 Wort
- Forecast6 Wörter
- Recommendations54 Wörter
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