Data Analyst

Sri Vyshnavi Gopalam



Data Analyst proficient in Python, SQL, PowerBI, Tableau, and Machine Learning, with a strong foundation in statistics and data visualization
@LinkedIN_Sri @GitHub_Sri

Automati Data Analysis Project

This project includes a series of comprehensive case studies, covering essential data analysis techniques such as Exploratory Data Analysis (EDA), Hypothesis Testing(AB), Multiple linear Regression Analysis, Machine Learning Model Development, and the Presentation of Findings.

Key Skills: EDA, AB testing, Regression Analysis, Machine Learning, Data Visualisation, PACE framework

Key Technologies: Python, Tableau

Tik Tok Data Analysis Project

This project consists of different individual case studies that covers Exploratory Data Analysis (EDA), Hypothesis Testing, Regression analysis, Multivariate Hypothesis Testing, Building a ML model and Presentation of findings

Key Skills: EDA, AB testing, Regression Analysis, Machine Learning, Data Visualisation, PACE framework

Key Technologies: Python, Tableau

Waze Data Analysis
Project

This project consists of different individual case studies that covers Exploratory Data Analysis (EDA), Hypothesis Testing, Logistic Regression Model to predict customer churn, Building a ML model and Presentation of findings

Key Skills: EDA, AB testing, Regression Analysis, Machine Learning, Data Visualisation, PACE framework

Key Technologies: Python, Tableau

Sales Analysis PowerBI
Dashboard

A comprehensive dashboard for analyzing automotive sales trends which provide a detailed breakdown of (YTD)figures, weekly trends, and sales by dealer/region. Also help's to keep track of important KPI's while empowering users to uncover hidden patterns and opportunities within the automotive sales landscape in a more granular level.

Goals Scored in Men's vs. Women's FIFA World Cup Matches

This project performs AB testing to determine if women scored more goals than men in FIFA World Cup matches. Using the Wilcoxon-Mann-Whitney test, we analyze scoring data from the past years performance to ascertain any significant differences between the two genders' performance in the tournaments.

Customer Segmentation using kmeans in
Python

This project uses unsupervised ML model K-means clustering to categorize customers based on shopping patterns. By identifying customer groups, we can tailor targeted marketing campaigns to enhances customer satisfaction and loyalty by delivering personalized experiences aligned with diverse needs.

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