Explore insightful retail analysis of Sample Store with comprehensive data and visualizations. Gain valuable insights into sales trends, customer behavior, and more. Dive into the data-driven world of retail with our analysis.
Project Overview
This Visualization provides an overview of the project, which involves conducting a retail analysis of Sample Store. The analysis includes importing customer data with 7 queries and a data model table, incorporating key performance indicators (KPIs) and measures. Additionally, the Sample Superstore data XLSX file was synchronized to enhance the analysis. This slide sets the stage for the project and highlights its key components.
IT Spend Analysis in Power View
)
In the IT Spend Analysis project, I utilized Power View to create effective visualizations, adjusting my approach to overcome any limitations encountered with unsupported visuals in Power BI. By identifying and removing incompatible visual types, I ensured the continuity and accuracy of the analysis. The revised file, named "IT Spend Analysis Sample.pbix," highlights my proficiency in adapting visualization tools to meet analytical requirements. This project showcases my capability to navigate and resolve data visualization challenges dynamically.
Sample Superstore Monthly Sales Analysis
This Visualization showcases the monthly sales analysis of Sample Superstore, featuring various visualizations aimed at providing comprehensive insights. The visuals include a District Manager list displaying sales variance by fiscal month, comparisons between last year's sales and current year's sales by fiscal month, and the total sales variance percentage by category for the current year. Through these visualizations, key trends and performance metrics are highlighted, offering valuable insights into the store's sales dynamics over time.
New Stores Analysis
This Visualization presents an analysis of new stores, beginning with a map visualizing store locations by city and chain. Following this, the analysis includes a depiction of open store count by open month and chain, providing insights into the distribution and growth of new stores over time. Additionally, a line graph illustrates this year's sales by fiscal month, offering a temporal perspective on sales performance. Lastly, a list of store names further contextualizes the analysis, providing a comprehensive overview of new store dynamics.
KPI Analysis and Sales Composition
Both slide visualization provides a comprehensive analysis of key performance indicators (KPIs) and sales composition for Fashions Direct and Lindseys Chain. The first visualization compares total units sold this year and last year by fiscal month, offering insights into unit sales trends over time. The second visualization presents a pie chart illustrating the sales composition for each chain, distinguishing between regular sales units and markdown sales units. Together, these visualizations offer a holistic view of performance dynamics and sales distribution for both chains.
This slide presents a comparative analysis of this year and last year's performance for Fashions Direct and Lindseys Chain. A column chart visually depicts the performance trends over time, enabling easy identification of variances and trends. Filter buttons facilitate focused exploration within specific chains, enhancing granularity.
Incorporating a multi-row card with an arrow button, this slide offers drill-through functionality for detailed insights. Users can Ctrl + click on specific data points to delve deeper into underlying factors influencing performance variations. Seamless transition between slides allows for a comprehensive analysis, combining high-level trends with detailed examination for informed decision-making.
Sales by Category Analysis
This slide presents an analysis of sales by category, featuring a stacked bar chart visualization. The chart provides insights into sales distribution across different categories, allowing for comparison and trend analysis. Two filter tabs are included for chain and buyer, enabling users to dynamically filter and explore sales data based on specific criteria. This visualization empowers users to gain a deeper understanding of sales patterns and make data-driven decisions.
To view the reports, download the .pbix file and open it using PowerBI Desktop.
The data used for analysis is sourced from an Sample Super Store data.
This project is licensed under the MIT License.