Maven Market Analysis

The story behind the work

I completed Maven Market Analysis as a bonus project in the Microsoft Power BI Desktop for Business Intelligence certification. Using the fictional retail dataset, I organized the reporting around three stakeholder questions: how the business is performing overall, which products drive results, and who its customers are.

What I set out to do

• Monitor sales, revenue, profit, transactions, margins, returns and business targets.
• Compare profitability and sales outcomes by product, brand and geography.
• Explore customer purchasing patterns using demographic and location segments.
• Deliver three connected Power BI pages with filtering and drill-through.

From raw data to a useful result

Transformed data with Power Query, modeled related tables and created DAX measures for revenue, margins, returns and targets.

• Connected to the supplied retail tables, checked data quality and applied transformations in Power Query.
• Built a relational model linking sales activity to products, customer attributes and location information.
• Created DAX calculations for revenue, profit margins, returns and comparisons with monthly targets.
• Designed an executive summary showing transactions, period comparisons, revenue trends and geographic performance.
• Developed dedicated product and customer pages for deeper investigation using interactive filters and drill-through.

What I contributed

Independent Power BI modeling, KPI definitions and summary/product/customer report design.

• Created the complete model and three-page report independently as part of the certification exercise.
• Designed the Product Details page to compare current-month profit and units sold against targets, while surfacing return-rate changes and leading brands.
• Used the Customer Details page to explore revenue and orders alongside occupation, gender, age and location groupings.

What the analysis revealed

• The Summary page combined sales, profit, transactions, margin and returns with weekday/weekend and location-based comparisons.
• The Product Details page highlighted profit and unit targets, monthly returns, weekly profits and top-performing brands and products.
• The Customer Details page compared purchasing behavior and customer contribution by demographic group and location.
• These views demonstrate the analytical coverage of the sample dataset; they are not a report of actual changes to a retailer’s performance.