Assignment 5-A

Power BI Dashboard Project

Design and build an interactive Power BI dashboard with advanced data modeling, custom DAX measures, and professional visualizations to support business decision-making.

7-8 hours
Advanced
100 Points
Submit Assignment
What You'll Practice
  • Designing data models in Power BI
  • Writing and optimizing DAX formulas
  • Creating interactive visualizations
  • Building professional dashboards
  • Implementing drill-down and filtering
Contents
01

Assignment Overview

In this assignment, you will build a complete Business Intelligence Dashboard for RetailTech, a growing retail company. This comprehensive project requires you to apply ALL concepts from Module 5: data modeling, DAX formulas, interactive visualizations, slicers, drill-down paths, and dashboard design best practices.

Power BI Desktop Required: You must use Microsoft Power BI Desktop (free version available). Power BI Service online has limited features for this assignment.
Skills Applied: This assignment tests your understanding of Data Modeling (Topic 5.3), DAX Fundamentals (Topic 5.4), and advanced Power BI dashboard creation.
Data Modeling (5.3)

Star schema, relationships, cardinality, optimization, performance

DAX Formulas (5.4)

Measures, calculations, time intelligence, CALCULATE, context

Visualizations & Design

Interactive charts, slicers, drill-down, formatting, polish

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02

The Scenario

RetailTech Analytics

You have been hired as a Business Intelligence Developer at RetailTech, a retail company that needs an advanced analytics dashboard. The director has given you this task:

"We have data in multiple formats and our leaders need real-time insights into sales, customers, inventory, and web analytics. Build a professional Power BI dashboard that they can drill down into, filter by date and region, and explore on their own. This will be used in weekly leadership meetings."

Your Task

Create a Power BI file called RetailTech_Dashboard.pbix that loads data from CSV files, creates a professional data model with proper relationships, implements advanced DAX measures, and builds five interactive dashboard pages with slicers and drill-down capabilities.

03

The Datasets

You will work with FOUR datasets containing RetailTech's operational data. Load these into Power BI and establish proper relationships.

File 1: retailtech_sales.csv (Sales Transactions)

Transaction-level sales data with 15,000 records spanning 2023-2024 across multiple regions.

  • OrderID, OrderDate, CustomerID, ProductID
  • Quantity, UnitPrice, Discount, TotalAmount
  • Region, Territory, Channel (Online/Retail)

File 2: retailtech_customers.csv (Customer Profiles)

Customer profile data with 2,500 records including demographics and engagement metrics.

  • CustomerID, Name, JoinDate, Segment
  • TotalPurchases, LifetimeValue, LastPurchaseDate
  • City, Region, PreferredChannel

File 3: retailtech_products.csv (Product Catalog)

Product catalog with 500 products across 8 categories including cost and inventory data.

  • ProductID, ProductName, Category, SubCategory
  • ListPrice, CostPrice, CurrentStock, ReorderLevel
  • Supplier, LastRestockDate

File 4: retailtech_webanalytics.csv (Web Metrics)

Daily website metrics with 730 days of traffic, conversion, and funnel data.

  • Date, DayOfWeek, Sessions, Users, PageViews
  • BounceRate, AvgSessionDuration, TrafficSource
  • ProductViews, CartAdditions, Checkouts, Purchases
04

Requirements

Your RetailTech_Dashboard.pbix must implement ALL of the following requirements. Each part is mandatory and will be tested individually.

1
Data Modeling & Preparation (20 points)

Load all four CSV files and create a professional data model:

  • Import and clean data with proper data types (dates, numbers, text)
  • Create relationships: Sales to Customers, Sales to Products, Sales to Date
  • Set cardinality correctly (1:Many, etc.) and cross-filter direction
  • Create a Date dimension table and mark as date table
  • Optimize and validate the model for performance
2
DAX Measures & Calculations (25 points)

Implement essential business measures using DAX formulas:

  • Sales Metrics: Total Revenue, Gross Profit, Profit Margin %, Revenue Growth %
  • Customer Metrics: Customer Count, New Customers MTD, Average LTV, Repeat Purchase Rate
  • Inventory Metrics: Total Stock Value, Stockout Risk, Inventory Turnover
  • Web Metrics: Conversion Rate, Cart Addition Rate, Bounce Rate %
  • Time Intelligence: Year-over-Year Revenue, Month-over-Month Growth, Running Total YTD
3
Dashboard Visualizations (30 points)

Create five professional dashboard pages:

  • Page 1 - Executive Summary: 4 KPI cards, Revenue Trend, Top 5 Products, Revenue by Region
  • Page 2 - Sales Analysis: Revenue by Channel, Top 10 Products, Sales by Territory, Daily Trend
  • Page 3 - Customer Analytics: Customer Segmentation, New Customers MTD, Distribution, Top 20 Customers
  • Page 4 - Inventory & Operations: Current Stock Value, Stockout Alert Table, Turnover by Category
  • Page 5 - Web Analytics: Conversion Funnel, Traffic by Source, Conversion Trend, Device Performance
4
Interactivity & Polish (15 points)

Add interactive features and professional formatting:

  • Slicers: Date range, Region, Customer Segment, Product Category
  • Drill-Down Paths: Region → Territory → City; Category → Subcategory → Product; Year → Quarter → Month
  • Formatting: Consistent color scheme, professional theme, clear titles, logical layout
  • Performance: Responsive design, fast filtering, optimized formulas
5
Documentation & Report (10 points)

Create comprehensive documentation:

  • Dashboard Overview: Executive summary with findings, screenshots, insights, recommendations
  • Data Model Documentation: Diagram/screenshot of relationships, table/column list, transformations
  • DAX Formula Reference: List of all measures with formulas and explanations
  • Usage Guide: How to use slicers, drill-downs, tips for interpreting data
05

Grading Rubric

Component Points Criteria
Data Modeling & Preparation 20 Correct data types, proper relationships, optimized model, clean data
DAX Measures & Calculations 25 All measures created, correct formulas, time intelligence implemented, KPIs accurate
Dashboard Visualizations 30 All 5 pages complete, appropriate chart types, visuals are clear and informative
Interactivity & Polish 15 Slicers functional, drill-down works, professional design, good performance
Documentation & Report 10 Complete documentation, clear explanations, screenshots included
Total 100
Deductions
  • -5 points: Missing or broken relationships in data model
  • -5 points: Incorrect DAX formula logic or results
  • -10 points: Missing required visualizations or pages
  • -5 points: Slicers or filters not functioning correctly
  • -10 points: Poor performance or dashboard hangs when filtering
  • -5 points: Incomplete or missing documentation
  • -5 points: Inconsistent formatting or unprofessional design
Bonus Points (up to 10)
  • +3 points: Advanced features (bookmarks, drill-through pages, custom visuals)
  • +3 points: Machine learning visualizations (forecasting, clustering)
  • +2 points: Mobile/responsive design optimization
  • +2 points: Exceptional design with branded colors and custom layouts
06

Submission

Create a public GitHub repository with the exact name shown below, add all required files, and submit through the submission portal.

github.com/<your-username>/powerbi-analytics-dashboard

Make sure your repository name matches exactly as shown above

Submit Assignment
Required Files Checklist:
  • RetailTech_Dashboard.pbix
  • Dashboard_Overview.pdf
  • Data_Model_Documentation.docx
  • DAX_Formulas_Reference.txt
  • Usage_Guide.pdf
  • README.md
  • CSV data files (if allowed by assignment)
  • .gitignore with *.pbix backup exclusions

All documentation files are required. Submission will fail if any file is missing.