Using Python Pandas Library to Analyze Sales Data

The Super Store dataset contains data on order details of customers for orders of a superstore ie; chain of multiregional stores under a brand globally. This is a detailed analysis on customer behavior analysis.

This is an analysis made on a superstore to understand why they had been making losses over a four year period, yet it had accounts on a substantial amount of sales over the same year period.

EDA is Exploratory and Explanatory Data Analysis. Global Super Store from Kaggle.com . Superstores industry comprises of companies that operateby having large size spaces which store and supply large amounts of goods.

A SQL repo for understanding analytics from basics to advanced with the help of Super Store datasets. It contains SQL dump of Super Store Dataset provided by Tableau and various questions.

This is my Power BI Project for the Master Program

“Power BI dashboard analyzing Superstore sales, profit and margins by region, category, and segment.”

Repository for Customer Segment Analysis using Python & Shiny App Dashboard

Case Superstore desenvolvido no Power BI

Business intelligence project capturing descriptive and predictive analytics

Internship_Project_DataAnalysis

Plateforme de prédiction des bénéfices de vente (Superstore) avec modèle Machine Learning. Composée d'une API backend (FastAPI) et d'un tableau de bord interactif (Streamlit).

This project provides an interactive analysis of Superstore sales data using Tableau, offering insights into sales performance, customer behavior, and market trends to help optimize business strategies.

Course Work (Project)

A chatbot poc using chatgpt api. Text to SQL chatbot with streamlit interface

TASK-3 by "THE SPARK FOUNDATION" EDA on dataset "SAMPLESUPERSTORE"

Using the Superstore dataset, the goal of this machine learning project is to perform Exploratory Data Analysis (EDA) and implement clustering techniques to gain insights into customer behavior and optimize the store's operations.

Fully interactive Tableau dashboard with parameter actions, dynamic metric switching & state highlighting — built on Sample Superstore dataset

This project applies RFM (Recency, Frequency, Monetary) analysis to segment SuperStore customers based on purchasing behavior. The goal is to support marketing campaigns by identifying loyal, promising, and at-risk customers using Python.