This project analyzes the AdventureWorks sales dataset to uncover key business insights related to sales performance, product trends, and customer behavior. The analysis is presented through interactive Power BI dashboards designed to help stakeholders monitor KPIs, identify growth opportunities, and make data-driven decisions.
- Tools used: Power BI, Microsoft SQL Server
- Lack of visibility into overall sales performance
- Difficulty identifying top-performing products and categories
- Need to track revenue trends and customer purchasing behavior
3.1 Sales Overview
- Total revenue, orders, and customers
- Sales trends over time (monthly / yearly)
- Revenue growth (YoY %)
- Regional or category-level performance
- Overall business performance snapshot
3.2 Product Analysis
- Top-performing products by revenue and quantity
- Product category and subcategory performance
- Identification of low-performing products
- Contribution of each product to total sales
- Profitability analysis across products
- Description: Star Schema
- Screenshot:
- Description: Provides a high-level summary of business performance.
- Screenshot:
- Description: Focuses on product-level insights and performance.
- Screenshot:
- Data cleaning and transformation (handling nulls, duplicates)
- Building an optimized data model (Star Schema)
- Creating accurate time intelligence measures (YoY, MoM)
- Ensuring dashboard performance and usability
- The business shows consistent revenue growth with seasonal fluctuations.
- A small number of products contribute to a large portion of total revenue (Pareto effect).
- Microsoft Power BI
- Microsoft SQL Server
- Data modeling, DAX measures, calculated columns