This project was initiated to replace static sales reports with dynamic, interactive dashboards that provide clea

rer visibility into internet sales performance for 2025. The goal is to empower the sales team with real-time, filterable insights into what products are being sold, to whom, and how performance compares against the 2025 sales budget

• Extract and clean data from the AdventureWorks database using SQL.
• Build a Power BI dashboard to visualize key metrics and trends.
• Track actual sales against the 2025 budget.
• Allow filtering by product, customer, region, and sales period.
• Support data-driven decision-making across the sales team.

• AdventureWorks (SQL Server sample database)
• 2025 Budget Data (Excel sheet provided by Sales Manager)

• SQL Server Management Studio (SSMS): Used to write and execute SQL queries to extract and clean relevant data from the AdventureWorks database based on the project requirements.
• Microsoft Excel: Contained the 2025 sales budget used for comparison against actuals.
• Power BI: Used for both data modeling (relationships, calculated columns, and measures) and visualization (dashboards, filters, and KPIs.
• DAX (Data Analysis Expressions): Used within Power BI to calculate sales metrics, budget comparisons, and performance trends.
• GitHub – For project version control and sharing the dashboard documentation.

• Over 50% of internet sales come from a small customer group.
• Highlights a strong dependence on a small group of customers.

• Bikes consistently outperform other categories.
• Surpassed monthly budget targets by a significant margin.

• Fell short of 2025 budget by over 25%.
• Shows weak traction across most customer segments

• Q2 underperformed despite steady demand before and after.
• Affects year-to-date budget alignment

• These cities account for the highest revenue and customer count.
• Clear regional sales hotspots

• Personalize engagement strategies for key accounts.
• Prioritize retention, upselling, and exclusive offers

• Increase inventory, promotions, and marketing for bikes.
• Track performance by region and rep for deeper insights.

• Repackage accessories and clothing into bundles.
• Reassess pricing and visibility in marketing efforts

• Review supply chain, seasonality, and sales activities.
• Adjust future Q2 strategies accordingly

• Launch city-specific campaigns for London and Paris.
• Consider increasing the sales force or partnerships there.

• Date Misalignment: The budget and sales data covered different periods, causing inconsistencies in comparisons.
• Incomplete 2025 Sales Data: Sales records existed only for January 2025, while the budget spanned up to June.
• Customer Data Cleaning: Required SQL transformations like merging names, decoding gender, and linking city data