Sales Analysis for a Retail Company - AnalysisWithSadiul

Case study analysis is a crucial part of a Power BI project. It involves an analytical process where you analyze data based on a real-world problem or challenge. Below is the process and steps for analyzing a real-life case study:

 

Real life case study analysis

 Case Study: Sales Analysis for a Retail Company

 

 1. Case Study Introduction

 

- Context: A retail company wants to analyze its sales performance to understand which products, regions, and time frames have the highest sales.

- Objective: To improve business strategies by analyzing sales performance and providing insights for better decision-making.

 

 2. Data Collection

 

1. Identify Data Sources:

   - Data Sources: Excel file, SQL database, or cloud data sources.

   - Key Data Fields: Sales records, product descriptions, customer information, regional data, date, etc.

 

2. Collect Data:

   - Collect Data: Gather data from the identified sources and load it into Power BI.

 

 3. Data Analysis

 

1. Data Preparation:

   - Data Cleaning: Remove unnecessary columns and duplicate records.

   - Data Transformation: Merge data tables and create necessary custom columns.

 

2. Data Modeling:

   - Create Relationships: Establish relationships between tables, such as linking the Sales table to the Products and Customers tables.

   - Calculated Columns and Measures: Create measures and calculated columns such as Total Sales, Average Sales, and Sales Growth.

 

3. Time Intelligence:

   - YTD, QTD, MTD: Calculate Year-to-Date, Quarter-to-Date, and Month-to-Date sales.

 

 4. Visualization

 

1. Create Basic Visuals:

   - Sales Performance: Display product sales performance using a bar chart.

   - Regional Sales: Analyze region-based sales using a map visual.

   - Trend Analysis: Use a line chart to analyze sales trends over time.

 

2. Add Interactive Elements:

   - Slicers and Filters: Use slicers and filters to analyze sales by different time frames, product categories, and regions.

   - Drill-Through: Use the drill-through feature for detailed analysis.

 

 5. Report and Dashboard Creation

 

1. Report Page Design:

   - Layout: Design and arrange the layout of visuals properly.

   - Interactivity: Ensure interactivity between the visuals.

 

2. Create Dashboard:

   - Pin Visuals: Pin important visuals to the dashboard.

   - Tile Customization: Customize the dashboard tiles and add necessary extensions.

 

 6. Result Analysis

 

1. Analyze Information:

   - Performance Trends: Analyze the trends in sales performance.

   - Top Products: Identify the top-selling products.

   - Regional Insights: Analyze sales performance across different regions.

 

2. Business Strategy:

   - Recommendations: Provide recommendations to improve business strategies based on data analysis.

   - Actionable Insights: Deliver actionable insights for decision-making.

 

 7. Report Sharing and Collaboration

 

1. Publish Report to Power BI Service:

   - Publish: Publish the report to Power BI Service.

 

2. Dashboard Sharing:

   - Share: Share the report and dashboard with team members.

 

3. Collect Feedback:

   - Feedback: Collect feedback from users and update the report.

 

 8. Project Review

 

1. Review:

   - Review: Review various parts of the project and make necessary changes.

 

2. Implementation:

   - Implement: Make business decisions and take action based on the insights derived from the report.

 

Through this case study analysis, students will learn how to solve real-world problems using Power BI and improve their analytical skills.