Portfolio - Pranay Talware

About Me

Welcome to my portfolio! I’m an aspiring Data Analyst with a knack for turning data into insights using Excel, PowerBI, SQL, and Python. Even though I have a degree in Electrical and Electronics Engineering, I discovered my true calling in data analysis.

I've worked on several business projects, which you can see below, where I've used my skills to help solve real problems and make data-driven decisions. These experiences have given me a solid understanding of how to analyze complex data sets and present clear, actionable insights.

I'm also diving into data science, taking on projects to sharpen my abilities in machine learning and predictive analytics. I'm constantly learning and staying up-to-date with the latest tools and techniques to ensure I can provide the best solutions.

Thank you for checking out my work. I’m excited to connect with you and bring my passion for data to your team! Let’s turn data into your next big opportunity.

Key Skills

SQL

Python

Machine Learning

Statistics

Deep Learning

Excel

PowerBi

Tableau

Domain Knowledge

My Projects

Business Insights 360 Dashboard for Finance, Sales, Marketing and Supply Chain

Domain/Function: Data visualization

Sales Analytics

Domain/Function: FMCG

COVID-19 Data Exploration Using SQL

Domain/Function: COVID-19 Data Exploration

Nashville Housing Data Cleaning and Transformation

Domain/Function: Real Estate / Property Data Analysis

"Movie Magic: Uncovering Insights from Film Data"

Domain/Function: Data Analysis and Visualization

My Experience

Work Experience:

2022 Feb - PRESENT

Capgemini India - Data Analyst

(Key Achievements and Responsibilities):

Enhanced Data Collection Procedures: Developed a sophisticated reporting system using Python, SQL, and BI tools, automating daily, weekly, and monthly reports. Streamlined operations, saving 15 hours weekly and enhancing accuracy by 25%.

Data Transformation and Cleaning: Transformed and cleaned over 500,000 rows of data using Python, SQL, and Excel, resulting in a 40% more efficient exploratory data analysis process and a 25% reduction in data processing time.

Utilized Databases: Imported data from MySQL and Excel with over 1 million records and performed data modelling.

Statistical Analysis: Conducted model comparison using Logistic Regression, K-Nearest Neighbours (KNN), Decision Tree, and Random Forest, evaluating over 50 precision, recall, and F1-scores.

Data Visualization: Created compelling data visualizations using Matplotlib and Seaborn, presenting actionable insights through histograms, box plots, and scatter plots; reduced data analysis time by 40% for the analytics team.

Developed Business Intelligence Reports & Dashboards: Designed and maintained KPI dashboards using Power BI, enabling real-time tracking and reporting of business metrics.

Business Insights: Interpreted critical business KPIs and performance data; presented actionable insights that accelerated product development cycles by 25% and increased market flexibility by 30%.

Report Optimization: Optimized reports using DAX studio, saving 30% of storage and increasing performance by 10%.

Customer Satisfaction: Collaborated in a cross-functional team to improve customer satisfaction, resulting in a 50% increase in positive feedback and a 20% reduction in complaints.

Data Scientist

• Diabetes Prediction Model: Analysed a dataset of 768 instances to predict diabetes outcomes, achieving 76% accuracy using random forest classification.

• Data Visualization: Created compelling data visualizations using Matplotlib and Seaborn, presenting actionable insights through histograms, box plots, and scatter plots; reduced data analysis time by 40% for the analytics team.

• Model Comparison: Conducted model comparison using Logistic Regression, K-Nearest Neighbours (KNN), Decision Tree, and Random Forest, evaluating over 50 precision, recall, and F1-scores.

• Machine Learning Implementation: Implemented scikit-learn for machine learning model development and evaluation.

• Healthcare Insights: Developed comprehensive models identifying critical diabetes determinants like Glucose, BMI, Age, and Skin Thickness; enabled healthcare providers to tailor treatments, improving patient outcomes by 30%.

Pranay Talware

Hello, I am

Pranay Talware.

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