superstore-dataset

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.

SuperStore Business Intelligence Dashboard

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.

Deep-dive Jupyter notebooks covering Pandas, NumPy & Matplotlib — real-world data analysis & visualization using the Superstore dataset.

My first portfolio project showcasing data cleaning, analysis, and visualization of Superstore sales data.

Interactive Excel sales dashboard built with PivotTables, PivotCharts, and Slicers.

End-to-end Exploratory Data Analysis (EDA) project on Superstore Sales dataset including data cleaning, feature engineering, outlier handling, customer segmentation, and business insights using Python, Pandas, Matplotlib, and Seaborn.

An interactive sales dashboard developed using Power BI / Tableau to analyze key business metrics, identify trends, and support data-driven decision-making.

Interactive Excel Sales Performance Dashboard built with Pivot Tables, Pivot Charts, KPI Cards, Slicers, and Dynamic Filtering using the Superstore dataset.

Traced a ~20% discount threshold driving negative margins in a $2.3M business and published an interactive Tableau dashboard with targeted fixes.

Sales Trend and Profit Analysis using Python, Pandas, Matplotlib, and Seaborn to analyze business sales performance, profitability, product trends, and customer insights from the Superstore dataset.

An end-to-end Excel project: cleaned Superstore dataset and built an interactive sales dashboard to uncover key business insights.

Interactive Tableau dashboards analyzing sales performance and customer behavior to drive data-driven business decisions.

visualization of 2018-2021 superstore sample data in US

Created an interactive sales dashboard in Microsoft Excel using Pivot Tables, Pivot Charts, and slicers. Analyzed sales, profit, units sold, regional performance, product categories, and seasonal trends to uncover business insights and support data-driven decision-making.

Data Analytics internship project — retail sales analysis, RFM segmentation & business insights using Python, Pandas, and the SuperStore dataset (MashupStack, 2026)

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.

An end-to-end retail sales analytics project built using the Superstore Dataset (Kaggle), covering the full data pipeline from raw data ingestion to executive dashboard reporting. This project simulates a real-world business intelligence workflow including data warehousing, ETL processing, SQL analysis, and interactive Power BI visualization.

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.