Regional Sales Dashboard Power BI

Requirement Document for Regional Sales Dashboard Power BI

1. Introduction

The Regional Sales Dashboard in Power BI provides an analytical overview of sales performance across different regions. It enables users to track key metrics such as sales, profit, and quantity across four regions: Central, West, South, and East. The dashboard also provides insights into sales trends by month, customer segment, and product category.

2. Objective

The primary objective of this dashboard is to provide a comprehensive visualization of regional sales data, allowing stakeholders to:

• Monitor sales trends and performance across different timeframes.
• Analyze customer segment distribution and profitability.
• Track sales contributions from different product categories.
• Identify growth trends through Year-over-Year (YoY) comparisons.

3. Dashboard Components

The dashboard consists of multiple visual elements, each representing key insights:

3.1 Key Metrics Overview (By Region)

For each of the four regions (Central, West, South, and East), the following key performance indicators (KPIs) are displayed:

• Sales ($) and Year-over-Year (YoY) % change
• Profit ($) and Year-over-Year (YoY) % change
• Quantity of units sold and Year-over-Year (YoY) % change

3.2 Sales by Month

A line chart displays sales performance for each month (January to December), allowing users to analyze trends over time.

3.3 Sales by Customer Segment

A bar chart categorizes sales by different customer segments:

• Corporate
• Consumer
• Small Business
• Home Office

Each segment’s contribution to total sales is displayed numerically and graphically.

3.4 Sales by Product Category

A pie chart displays the percentage contribution of different product categories to total sales in each region.

4. Data Sources & Integration

• The dashboard pulls data from a structured sales database (e.g., SQL Server, Excel, or cloud-based data sources).
• Data refresh frequency: Daily/Weekly (as per business needs).
• Filters and slicers: Users should be able to filter the data by region, time period, customer segment, and product category.

5. Functional Requirements

1. Interactive Visuals:
   • Users should be able to click on a region and see sales breakdowns dynamically.
   • Hovering over data points should display tooltips with additional details.
2. Comparative Analysis:
   • Include Year-over-Year percentage changes for quick trend analysis.
   • Allow users to compare different time periods.
3. Performance Indicators:
   • Highlight regions with the highest and lowest sales/profit.
   • Use conditional formatting to indicate positive (green) and negative (red) trends.
4. Export & Sharing:
   • Provide options to export reports to PDF, Excel, and PowerPoint.
   • Allow integration with Power BI Service for cloud-based sharing.
5. Security & Access Control:
   • Implement role-based access control (RBAC) to restrict sensitive data.
   • Enable row-level security (RLS) for regional managers to view only their respective data.

6. Technical Requirements

• Power BI Desktop / Power BI Service for visualization and distribution.
• DAX Measures for calculating YoY percentage changes and KPIs.
• SQL Queries / Data Modeling to integrate data from various sources.
• Responsive Design for usability on desktops, tablets, and mobile devices.

7. Project Completion Method

The project will be completed using a combination of SQL Queries, Power Query, and DAX:

7.1 SQL Queries

• Data Extraction: Write optimized SQL queries to extract data from relational databases.
• Data Transformation: Use SQL functions to clean and normalize data before loading into Power BI.
• Joins and Aggregations: Implement necessary joins (INNER, LEFT, RIGHT) to merge tables for meaningful insights.
• Example Query: SELECT Region, CustomerSegment, ProductCategory, SUM(Sales) AS TotalSales, SUM(Profit) AS TotalProfit FROM SalesData WHERE OrderDate BETWEEN '2023-01-01' AND '2023-12-31' GROUP BY Region, CustomerSegment, ProductCategory;

7.2 Power Query (ETL Process)

• Data Cleaning: Handle missing values, remove duplicates, and format date columns.
• Data Transformation: Perform column renaming, data type changes, and calculations before loading data.
• Merging Queries: Combine multiple tables to create meaningful relationships.
• Automated Refresh: Schedule data refresh for real-time analysis.

7.3 DAX Calculations

• Key Performance Measures: Total Sales = SUM(SalesData[Sales]) Total Profit = SUM(SalesData[Profit]) YoY Sales Growth = VAR CurrentYearSales = CALCULATE(SUM(SalesData[Sales]), SalesData[Year] = YEAR(TODAY())) VAR LastYearSales = CALCULATE(SUM(SalesData[Sales]), SalesData[Year] = YEAR(TODAY()) - 1) RETURN DIVIDE(CurrentYearSales - LastYearSales, LastYearSales, 0)
• Dynamic Filters & Time Intelligence: Use slicers to allow users to interact dynamically with data.
• Conditional Formatting: Apply dynamic rules to highlight trends in reports.

8. Expected Outcomes

By implementing this dashboard, stakeholders will:

• Gain real-time insights into regional sales performance.
• Improve decision-making based on interactive and data-driven visuals.
• Identify growth opportunities and problem areas in different regions.
• Enhance business planning with trend forecasting and customer behavior analysis.

9. Conclusion

The Regional Sales Dashboard serves as a critical tool for monitoring sales and profitability. Its interactive and user-friendly interface will empower decision-makers with data-driven insights to optimize regional sales strategies effectively.

sample data files for your Power BI Regional Sales Dashboard:

1. Download Sample Sales Data
2. Download Sample Customer Segments
3. Download Sample Product Categories

These files contain structured data for Sales, Customer Segments, and Product Categories