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A complete hands-on practice repository for learning Pandas in Python. Covers data cleaning, missing data handling, merging & joining, row operations, updating values, descriptive analysis, and working with real datasets like Superstore. Ideal for beginners and data analysis learners.
An interactive sales dashboard developed using Power BI / Tableau to analyze key business metrics, identify trends, and support data-driven decision-making.
Executive-level Power BI dashboard built on the Superstore dataset using the .pbip project structure for version control and collaboration. Delivers quarterly sales insights across regions, product categories, and customer segments, with a clean semantic model and consistent design system.
Interactive Tableau Story analyzing Superstore sales data. Evaluates profitability across regions and cities, identifying high-value markets (e.g., California, New York) and underperforming areas to optimize revenue strategy.
This repository showcases various data analyses on the popular Superstore dataset using SQL queries. The analyses cover a range of business insights, including sales performance, customer segmentation, and product profitability. Each analysis is documented with the SQL queries used and explanations of the steps involved.
Interactive Power BI dashboard analyzing Superstore sales (2014–2017). Includes KPI cards, trend analysis, regional and category breakdowns, and drill-down filters to identify top-performing segments and business insights.
This is an Excel sales dashboard I built to clearly understand business performance including sales, profit, customer count, and trends across different categories and states.
Power BI Sales Analytics Project (Global Superstore Dataset) — full end-to-end analysis with DAX measures, semantic modeling, drill-through logic, and business insights.