https://github.com/sohamb21/analysis-of-superstore-dataset

I completed the IBM SkillsBuild Data Analytics Internship Program to develop my Data Analytics skills and apply them to a real-world problem by working on this project.
https://github.com/sohamb21/analysis-of-superstore-dataset

data-analysis python

Last synced: 5 days ago
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I completed the IBM SkillsBuild Data Analytics Internship Program to develop my Data Analytics skills and apply them to a real-world problem by working on this project.

• Host: GitHub
• URL: https://github.com/sohamb21/analysis-of-superstore-dataset
• Owner: SohamB21
• Created: 2023-07-10T15:35:33.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-07-10T16:41:03.000Z (over 1 year ago)
• Last Synced: 2024-12-25T14:25:39.677Z (about 2 months ago)
• Topics: data-analysis, python
• Language: Jupyter Notebook
• Homepage:
• Size: 1.02 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
**Analysis Of SuperStore Dataset**

This project focuses on analyzing the SuperStore dataset, which contains sales data from a fictional retail store. The goal of the analysis is to gain insights into the store's performance and identify areas for improvement.

**Project Summary**

1. Dataset Utilization: I conducted a comprehensive analysis of the SuperStore dataset, focusing on sales data, to gain valuable insights into the store's performance and identify areas for improvement.

2. Data Exploration and Preprocessing: I extensively explored the dataset, meticulously examining its structure, variables, and data quality to ensure accurate and reliable analysis results. Additionally, I performed data cleaning and preprocessing to enhance the integrity of the dataset.

3. Exploratory Data Analysis (EDA): Through thorough EDA, I uncovered meaningful patterns, trends, and relationships in the sales data. By delving into key performance metrics such as sales revenue, profit, and customer segments, I gained a comprehensive understanding of the SuperStore's performance.

4. Geographical Sales Analysis: I examined the geographical distribution of sales to identify potential target markets and optimize the store's marketing and expansion strategies.

5. ML Model Development: In addition to the analysis, I developed a regression-based machine learning model to predict profit. Leveraging advanced statistical techniques and powerful algorithms, the model enables accurate profit forecasting and assists in strategic decision-making.

I provided data-driven analysis, visualizations, and an ML model to enhance SuperStore's profitability and customer satisfaction. This project optimizes business operations, drives growth, and empowers stakeholders for informed decision-making.