This project focuses on building an end-to-end sales analytics solution using Microsoft Power BI. It covers data extraction from multiple sources such as Excel, SQL databases, and cloud services, followed by data cleansing and transformation using Power Query. A star-schema data model is designed to optimize performance, and DAX measures are created to calculate KPIs like total revenue, growth rate, and profit margins. Interactive dashboards and reports are developed to analyze sales by region, product, and time period. The solution enables business users to track performance trends and make data-driven decisions in real-time.

This project focuses on analyzing customer data to identify patterns, segments, and behavioral insights using Power BI. It involves preparing large customer and transaction datasets, applying data modeling best practices, and creating advanced DAX calculations such as customer lifetime value and retention metrics. AI visuals and key influencer analysis are used to uncover factors driving customer behavior. Interactive reports allow stakeholders to explore segments by demographics, purchase history, and engagement levels. The project reflects real-world marketing and business intelligence scenarios used by data-driven organizations.

This project focuses on designing an enterprise-level KPI monitoring and reporting system using Power BI. Operational data from multiple departments is transformed and modeled to track performance metrics such as efficiency, cost, and SLA adherence. Role-based and row-level security is implemented to ensure data privacy and controlled access for different users. Reports are published to Power BI Service with scheduled refresh and dashboard alerts for key thresholds. The project demonstrates governance, security, and deployment practices commonly used in large corporate environments.