Agent skill · data analytics · aradotso
power-bi-retail-analytics-dashboard
Power BI retail sales dashboard for multi-dimensional profit, regional, and sales analysis with predictive insights
Why this skill is useful
Provides specific DAX measures and Power BI configurations that enhance retail analytics capabilities not commonly known to AI.
What it needs
Requires power bi installed locally. Requires power bi service account access. About 10k tokens when loaded. Last updated 2026-08-05. 5 stars on the source repository.
What this skill does
Power BI Retail Analytics Dashboard Skill Skill by ara.so — Data Skills collection. This skill enables AI coding agents to work with SalesPulse 360, a comprehensive Power BI retail analytics dashboard designed for multi-dimensional sales, profit, and regional analysis. The project transforms raw sales data into interactive visualizations with predictive forecasting, exception alerts, and multi-granularity filtering. What This Project Does SalesPulse 360 is a production-ready Power BI dashboard that: Visualizes retail performance across regions, product categories, customer segments, and time periods Provides predictive analytics using built-in Power BI forecasting for 12-month projections Generates automated alerts when KPIs breach configurable thresholds (profit margin, return rate) Supports multi-language localization with currency and date format adaptation Enables drill-down analysis from global summaries to individual transaction details Auto-refreshes data on scheduled intervals via Power BI Service The dashboard is built on the Global Superstore dataset (2011-2015) but can be adapted to any retail/sales data source. Installation & Setup Prerequisites Power BI Desktop (version 2.120 or higher) - Download here Power BI Service account (for publishing and scheduled refresh) Modern web browser for viewing published dashboards Step 1: Clone the Repository Step 2: Extract Dataset The Global Superstore dataset is included as a compressed file: Step 3: Open the Power BI File On first load, Power BI Desktop will: 1. Connect to the CSV data source 2. Run Power Query transformations (data cleaning, normalization) 3. Load the data model (typically 2-3 minutes) Step 4: Update Data Source Path (if needed) If you've moved the dataset to a custom location: 1. Go to Home → Transform Data → Data Source Settings 2. Select the CSV source 3. Click Change Source 4. Update the file path to your CSV location 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/power-bi-retail-analytics-dashboard