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, ...
Source: DEV Community
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 an
