Power BI Projects: Global Superstore Analytics

Online shopping has become increasingly important, especially post COVID-19 pandemic, which limited physical store visits. Businesses must now rely heavily on data to understand customer behavior, optimize product performance, and improve operational efficiency. Using the Global Superstore dataset , the following are structured Power BI projects that demonstrate end-to-end analytics capabilities. Stage 1 Data Engineering & Ingestion Objective Build a scalable data pipeline by moving raw data into a database. Scope Import CSV/Excel data into: SQL Server / MySQL / PostgreSQL Create structured tables: orders customers products Connect Power BI to the database Stage 2: Data Cleaning & Transformation Prepare clean and reliable data for analysis using Power Query. Key Tasks Handle missing values (Postal Code, Discount anomalies) Remove duplicates (Order ID + Product ID) Fix data types (dates, numeric fields) Create derived columns: Delivery Days Profit Margin Standardize categories and count