Enhancing Insights:Survey Data Analysis with Power BI
Project
Enhancing Insights:Survey Data Analysis with Power BI
Titanic Dataset Visualization
Sentiment Analysis on Thread App Dataset using SVM and Random Forest Classifier
This project utilizes the "Thread App Dataset: 37000 Entities" to perform sentiment analysis on user reviews of the New Thread mobile application. SVM and Random Forest Classifier algorithms are employed, achieving accuracy rates of 84% and 82% respectively, providing insights into user satisfaction, usability, and feature preferences.
Web Scrapping
This project involves scraping data from the 2023 Fortune Global 500 list to extract the financial details of 14 Canadian companies for fiscal year 2022.
Boeing-Order&Deliveries
The main objective of this project is to perform exploratory data analysis (EDA) to identify patterns and trends within the dataset. By examining historical data, the project aims to uncover potential opportunities based on past trends.
Online Retail Data
SQL Analysis
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Email Campaign
Tableau Dashboard
This visualization enables trend monitoring, pattern identification, and data-driven decision-making. It helps optimize campaigns, compare performance, and set goals.
Super Store
EDA
This project involved performing EDA on the Superstore dataset using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn to gain insights into the data, identify patterns, trends, and relationships, and prepare the data for further analysis and modeling.