Make Margins Great Again - Superstore Sales Analytics

Make Margins Great Again - Superstore Sales Analytics

This report transforms the classic Superstore dataset (adapted) into a fully documented, enterprise-grade analytics solution built on a Fact Constellation Schema with two fact tables (Sales & Target), conformed dimensions and a normalised product hierarchy.

Key Features:

🎯 Dynamic KPIs — Revenue, Profit, Margin and Cost cards with SVG sparklines, YoY growth, target tracking and progress bars, all switchable between YTD, QTD and MTD via a TimeFilter parameter;

🌍 Geography Page — Revenue by state choropleth map, city efficiency scatter plot with K-Means clustering (6 segments: Small Markets, Contributors, Big Contributors, Flagship Cities, High Margin Cities, Margin Risk) and a detailed city-level matrix with trending indicators;

📦 Product Analysis — Sub-category efficiency scatter plot with K-Means product clustering (5 segments: Star Products, Niche Performers, Contributors, Core, Loss Drivers);

🔢 Dynamic Details Matrix — A fully flexible matrix with conditional formatting allowing one-click switching between dimension (Region, State, City, Category, Sub-Category), metric (Revenue, Profit, Margin, Cost, Shipping) and aggregation using field parameters — turning one visual into dozens of analytical views;

⚙️ Tariff Scenario Analysis — What-if modelling for tariff rates and price increases showing adjusted revenue, cost, profit and margin with a waterfall decomposition chart;

📖 Dynamic Data Dictionary — A fully searchable, filterable documentation page powered by INFO.VIEW() functions covering all measures, columns, tables and relationships with descriptions, DAX expressions and object type filtering.

Technical Highlights:

• Fact Constellation Schema with snowflake product dimension
• 80+ DAX measures with full descriptions via TMDL
• SVG sparklines and progress bars as ImageUrl calculated measures
• Field parameters for dynamic dimension, metric and aggregation switching
• Target data sourced from 5 separate CSVs merged into a single Target Table
• Single staging query ETL pattern in Power Query
• Full semantic model documentation via TMDL descriptions

Here you can download the PBIX file.

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