1.1 Purpose
The Retail Sales Dashboard provides insights into key sales performance metrics, including total sales, orders, profit, and regional distribution. The goal is to enable business stakeholders to analyze sales trends, identify profitable product categories, and optimize retail strategies.
1.2 Scope
This dashboard is designed for retail managers, sales teams, and business executives to track sales performance across different product categories, subcategories, manufacturers, and regions. It facilitates real-time decision-making for better revenue growth and profitability.
1.3 Audience
- Retail Managers
- Sales Teams
- Business Executives
- Financial Analysts
2. Dashboard Features & Functionalities
2.1 Sales Performance Metrics
- Total Sales
- Total Orders
- Total Profit
- Year-over-Year (YoY) Sales Growth
- Sales Performance by Category & Sub-Category
- Sales by Segment (Home Office, Corporate, Consumer)
- Sales by Manufacturer
2.2 Regional Sales Insights
- Sales by Region (Central, East, South, West)
- Sales Trends vs. Previous Year (PY)
- State-wise Sales Performance
2.3 Product-Level Sales Analysis
- Sales by Category (Office Supplies, Technology, Furniture, etc.)
- Monthly Sales Breakdown by Sub-Category
- Manufacturer-wise Sales & Growth Analysis
2.4 Filtering & Segmentation
- Year Selection (2020, 2021, 2022, 2023, etc.)
- Category & Sub-Category Selection
- Region & State Selection
- Manufacturer Selection
3. Data Sources & Integration
- Point of Sale (POS) System
- Enterprise Resource Planning (ERP) System
- Customer Relationship Management (CRM) System
- E-commerce Sales Data
4. User Requirements
4.1 Functional Requirements
- Ability to filter sales data by year, category, region, and manufacturer
- Interactive visualizations for sales trends and profitability analysis
- Exportable reports for sales review meetings and business strategy planning
- Automated data refresh for real-time insights
4.2 Non-Functional Requirements
- Performance: Ensure dashboard loads within 5 seconds
- Security: Implement role-based access control to protect sensitive sales data
- Scalability: Support increasing transaction volumes and product categories
5. Key Performance Indicators (KPIs)
- Total Sales & Profit Growth
- YoY Sales Comparison
- Sales by Category & Sub-Category
- Regional Sales Trends
- Sales by Manufacturer & Market Share
- Average Order Value
6. Assumptions & Constraints
- Data should be sourced from reliable sales and transactional systems
- User access should be managed based on sales and finance roles
- Historical sales data availability might be limited for trend analysis
7. Project Completion Method
7.1 SQL Queries
- Extract sales and order data from multiple databases.
- Perform data transformations for trend analysis and profitability tracking.
- Example SQL Query for Sales Performance:
SELECT Year, Category, SubCategory, Region, SUM(Sales) AS TotalSales, SUM(Profit) AS TotalProfit, COUNT(OrderID) AS TotalOrders FROM SalesData WHERE Year = 2023 GROUP BY Year, Category, SubCategory, Region; - Queries to calculate profit margins, manufacturer performance, and regional sales trends.
7.2 Power Query
- Connect Power BI to SQL databases and sales systems.
- Perform ETL (Extract, Transform, Load) operations:
- Data cleansing (handling missing values, removing duplicates)
- Merging sales and order data from different sources
- Creating calculated columns for profit margins and growth rates
- Example Power Query transformation:
let Source = Sql.Database("ServerName", "DatabaseName"), SalesTable = Source{[Schema="dbo", Item="SalesData"]}[Data], FilteredRows = Table.SelectRows(SalesTable, each [Year] = 2023) in FilteredRows
7.3 DAX (Data Analysis Expressions)
- Create calculated measures for sales growth and profitability analysis.
- Example DAX formula for YoY Sales Growth:
YoY Sales Growth = DIVIDE( SUM(SalesData[Sales]) - SUM(SalesData[Sales PY]), SUM(SalesData[Sales PY]) ) - DAX measures for tracking top-selling products, best-performing regions, and profit margins.
8. Conclusion
The Retail Sales Dashboard provides comprehensive insights into sales performance, profitability, and market trends. It enables businesses to make data-driven decisions to improve revenue growth and optimize product strategies. The dashboard will evolve based on business needs and user feedback.
sample data files for the Retail Sales Dashboard, including:
- Sales Data (CSV) – Total sales, orders, profit, and category-wise distribution.
- Regional Sales Data (CSV) – Sales performance by region and state.
- Manufacturer Sales Data (CSV) – Sales and growth percentage by manufacturer.
Developed by Muhammad Zahid
