📊 Power BI: Customer & Sales Intelligence Report A comprehensive Power BI dashboard analyzing sales performance, customer demographics, and distribution channel efficiency (E-shop vs. Brick-and-mortar stores). This project demonstrates data modeling, DAX measures, and interactive storytelling.
🇬🇧 English Version 🎯 Project Overview This report provides a 360-degree view of a retail business's health. It bridges the gap between raw CSV data and actionable business insights, focusing on revenue trends and customer behavior across different regions and sales channels.
✨ Key Features & Pages Executive Summary: High-level overview of critical KPIs (Total Revenue, Customer Count, New Acquisitions).
Channel Performance: Comparative analysis between E-shop and physical stores, including a geographic map of branches.
Customer Demographics: Deep dive into age, gender, and loyalty status (New vs. Returning).
Granular Insights: Detailed transaction tables with advanced filtering and sparkline visualizations for trend spotting.
🛠️ Technical Details Tool: Power BI Desktop
Data Sources: Structured CSV files (Customers, Sales, Stores, Products, Exchange Rates).
Data Modeling: Star schema implementation with a dedicated Date dimension.
Logic: Custom DAX measures for calculating growth and performance indicators.
🚀 How to View the Project Clone or download this repository.
Open project_report.pbix using Power BI Desktop.
Note: If you wish to refresh data, ensure the /data/ folder path is correctly mapped in the Power Query editor. Otherwise, you can view the existing visuals with cached data.
🇨🇿 Česká verze 📌 Popis projektu Tento Power BI projekt se zaměřuje na komplexní analýzu prodejů a zákaznických dat. Sleduje výkonnost distribučních kanálů a pomáhá pochopit demografické složení zákaznické báze.
✨ Klíčové metriky a vizualizace Revenue & Growth: Sledování vývoje tržeb v čase.
Analýza kanálů: Srovnání úspěšnosti e-shopu oproti kamenným pobočkám.
Segmentace zákazníků: Přehled o věku, pohlaví a loajalitě nakupujících.
Datový model: Čistě navržený hvězdicový model pro efektivní výpočty.
📈 Data Structure / Datová struktura The report is powered by a relational model consisting of:
customer.csv – Demographic details and regions.
sales.csv – Transactional data (quantities, prices, channels).
store.csv & product.csv – Master data for dimensions.
currencyexchange.csv – Supporting table for financial conversions.
💡 Tip pro sekci "About" na GitHubu: Interactive Power BI dashboard for retail sales and customer analytics. Features Star schema modeling, DAX metrics, and multi-page business insights.
🐍 Příklad DAX (v angličtině) Pokud máš v projektu nějaké zajímavé DAX vzorce, můžeš je do README přidat jako ukázku tvé práce s logikou:
Fragment kódu
// Calculate Year-over-Year Revenue Growth YoY Revenue Growth = VAR CurrentYearRevenue = [Total Revenue] VAR LastYearRevenue = CALCULATE([Total Revenue], SAMEPERIODLASTYEAR('Date'[Date])) RETURN DIVIDE(CurrentYearRevenue - LastYearRevenue, LastYearRevenue, 0) 👤 Autor / Author: Adam Seifert
Kontakt: seifert.promotion@gmail.com