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Jisan Nuren Siam
Jisan Nuren Siam

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Data Science & AnalyticsPower BI · Business intelligence

Retail Sales Analysis

A self-directed Power BI project: turning a sample retail dataset into a report a manager could move through, from overview to store-level detail.

Overview graphic of the Power BI case study: the five-table model, the eight report pages and a store sales overview page with a channel donut, monthly variance bars, a store map and a variance scatter plot.
Fig. 01 — Project overview
Role
End-to-end build: data model, DAX measures, report design and page structure.
Type
Self-directed portfolio project
Status
Completed · sample dataset
Tools
Power BI · DAX · Star schema
Dataset
Sample / demo
Data model
5 tables
Report
8 analytical pages
Project type
Self-directed

Case study

01Brief

Built for decision support

The goal was a report structured around the questions a retail manager asks (how sales are trending, which stores and districts need attention, how this year compares with last) rather than a single page of every available chart.

02Model

A five-table star schema

A Sales fact table connected to District, Item, Store and Time dimensions, with DAX measures for this-year, last-year and variance calculations.

Dashboard architecture graphic: a star schema with a Sales fact table and Store, Item, District and Time dimensions, plus seven analysis areas from sales performance to KPI monitoring.
Fig. 02 — Dashboard architecture

View full size: Dashboard architecture (opens in a new tab)

03Geography

Store and regional segmentation

Map and scatter views segment performance by store, district and region, separating new stores from existing ones and comparing sales per square foot against variance.

Store and geographic performance page with a store location map, monthly variance bars, a store-level scatter plot, sales by district manager, stores by type and regions by store count.
Fig. 03 — Store and geographic performance

View full size: Store and geographic performance (opens in a new tab)

04Variance

This year against last year

Variance is broken down by fiscal month, district manager and category, with regular and markdown sales separated.

Sales performance and variance page comparing this year with last year: KPI cards, sales by store type, a monthly trend, a store map, variance by district manager and regular versus markdown sales by category.
Fig. 04 — Sales variance analysis

View full size: Sales variance analysis (opens in a new tab)

05Report structure

Eight pages, one path through the data

  • Overview
  • District monthly sales
  • New stores
  • KPI
  • Regular vs markdown
  • This year / last year / variance
  • Drill-through
  • Sales by category
Executive summary of the report's capabilities: multi-page reporting, data model relationships, DAX variance measures, slicers, drill-through, geographic analysis, KPI reporting and category analysis.
Fig. 05 — BI executive summary

View full size: BI executive summary (opens in a new tab)