Superstore Analysis for Power BI is a project that aims to provide insights into the sales and profit performance of a US-based online retailer. The project uses Power BI, a data visualization and business intelligence tool developed by Microsoft, to create interactive reports and dashboards from the Superstore retail transaction data. The data contains information about the orders, customers, products, sales, and profits of the Superstore.
The project covers the following aspects of data analysis:
Data import and cleaning:
The project uses Power Query Editor, a feature of Power BI, to connect to the data source, transform and shape the data, and resolve any data quality issues.
Data exploration and visualization:
The project uses Power BI Desktop, a free application that lets users create and publish reports, to explore the data and create various charts and graphs to visualize the sales and profit trends, patterns, and outliers.
Data modeling and calculation:
The project uses Data Analysis Expressions (DAX), a formula language for Power BI, to create measures, calculated columns, and tables that enhance the data model and support the analysis.
Data storytelling and presentation:
The project uses Power BI Service, a cloud-based platform that lets users share and collaborate on reports and dashboards, to publish the report and create a user-friendly dashboard that answers the key business questions and provides actionable insights.
Consider the sample data of Retail Sales to design the below dashboard visuals
1. Design a visual to display Sales and Profit by Segment
2. Design a visual for Order Priority by Sales
3. Add a List filter for Market and Segment (hint: Update the data source for Market column)
4. Add a filter for Order Date (hint: label it as Choose Date)
5. Highlight top 5 customers by Sales
6. Profit by Sales (design a Map)
7. Profit by Year and Quarter (hint: consider a Line chart)
- Add a card for Total Ship Price
9. Create a drill-through approach for Sales by Category and Region
- Add a List Country Filter (hint: Update the data source for the Country column)