Dashboard Link - https://app.powerbi.com/links/5SrPs2kGHX?ctid=a1a4ee51-99fa-437d-8ba7-d05192f6c077&pbi_source=linkShare
Power BI Capstone Project Overview The Power BI Capstone Project is an end-to-end business intelligence project designed to demonstrate the process of turning raw data into actionable insights using Power BI. This project integrates essential data analytics techniques, including data extraction, preprocessing, and visualization, to provide stakeholders with a clear understanding of trends, patterns, and decision-making metrics. Below is a detailed description of the project's process and methodology.
- Project Objective The primary goal of this project is to create a dynamic Power BI dashboard that provides insights into a dataset extracted from multiple sources. The dashboard enables stakeholders to make informed decisions based on key performance indicators (KPIs), trends, and forecasts.
The aim of the project was to create a report using default visuals, AI visuals, etc., to get key insights from the business which helps in strategic planning for the future.
Extracted data from Excel, performed various transformations in Power Query and injected it into the Power BI Desktop.
Designed a Star Schema data model, performed calculations using DAX functions created Quick Measures also Implemented Row-level-Security, and published BI report to Power BI Service in order to create a Dashboard.
Based on the report, the United States, Canada, and Australia were the top 3 countries with the highest number of sales, and bikes are the highest-selling category
- Data Extraction The first step involved extracting data from various sources, including:
Excel Files: The primary data source was an Excel workbook containing multiple sheets with structured data. External Databases: Additional data, if needed, was imported using Power BI's connectors for SQL Server or other databases. Online Data: Public datasets (e.g., CSV files) were integrated to enhance the analysis with supplementary information. This process ensured the dataset was comprehensive and relevant for the analysis.
- Data Loading After extraction, the data was loaded into Power BI. This step required setting up the Power Query interface for initial data exploration. Key considerations included:
Merging multiple tables to create a unified dataset. Setting relationships between different tables using Power BI’s data modeling features. 4. Data Preprocessing (Power Query) The preprocessing stage was executed in Power Query, which is an integral part of Power BI. Steps included:
Handling Missing Data: Replacing null values with defaults or averages. Removing Duplicates: Ensuring data consistency by identifying and eliminating duplicate entries. Transforming Columns: Adjusting data types, renaming columns, and creating calculated columns for better analysis. Splitting Columns: Extracting meaningful segments from combined data fields (e.g., splitting full names into first and last names). Merging Queries: Combining datasets with different dimensions using inner, outer, or left joins. This step ensured the dataset was clean, structured, and ready for analysis.
- Data Visualization The core of the project involved creating intuitive and interactive visualizations using Power BI’s drag-and-drop interface. Key steps included:
Building Dashboards: Designing an engaging and visually appealing layout with slicers, cards, and charts. Charts and Graphs: Utilizing bar charts, line graphs, pie charts, and scatter plots to represent KPIs, trends, and distributions. Filters and Slicers: Adding interactivity to dashboards, enabling users to drill down into specific data points. Calculated Measures: Creating custom DAX measures to derive insights, such as total sales, profit margins, or growth percentages. 6. Insights and Analysis The interactive dashboard provided actionable insights, such as:
Identifying top-performing categories or regions. Analyzing trends over time to forecast future growth. Detecting anomalies or outliers in sales and performance data. 7. Final Presentation The project concluded with the delivery of a polished Power BI dashboard, supported by a detailed presentation. This included:
Summary of Findings: Highlighting key insights for stakeholders. Interactive Demonstration: Guiding users through dashboard functionalities.