About Me

I am a passionate data analytics professional with a solid academic foundation in data analysis, currently pursuing a Master's in Data Analytics and Information Systems Management. Throughout my academic journey, I have focused on advanced statistical methods, data visualization techniques, and machine learning applications to solve complex problems. My coursework and projects have equipped me with hands-on experience in analyzing large datasets, creating insightful visualizations, and using analytical tools to derive actionable insights. Building on my strong foundation in full-stack development, particularly with the Java Spring Framework, I have also honed my skills in designing APIs, integrating databases, and enhancing workflows. This technical background complements my transition to data analytics, enabling me to approach data-driven challenges with a unique blend of development and analytical expertise. I am eager to contribute my skills to a dynamic organization where I can help drive strategic decisions through data insights. By the way, check out my awesome work.

Projects

Bank Marketing Campaign Analysis using Python

Analyzing a bank's marketing campaign data to predict future campaign outcomes and build customer profiles for term deposit services. The dataset includes demographic details (age, job, marital status, education), campaign information (contact number, previous outcomes), and economic indicators. The goal is to use this data to forecast the success of future campaigns and identify characteristics of potential customers who are more likely to accept a term deposit offer. The analysis aims to provide actionable insights for optimizing future marketing efforts.

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Amazon Reviews Sentiment Analysis using Python

Exploring customer sentiment analysis on Amazon reviews through three distinct techniques: VADER (Valence Aware Dictionary and Sentiment Reasoner), a lexicon-based approach; the RoBERTa pretrained model, leveraging transformer architecture for advanced sentiment prediction; and Hugging Face Pipelines for streamlined implementation of state-of-the-art natural language processing models. The project encompasses data preprocessing, sentiment classification, and performance evaluation, offering a comparative analysis of these methodologies. It also includes insightful visualizations and findings, demonstrating a comprehensive approach to understanding consumer feedback using modern AI tools.

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Sales & Customer Dashboard in Tableau

Developed an integrated dashboard that provides detailed insights into both sales performance and customer trends. The sales view showcases total sales, profits, and quantity sold, along with detailed analysis by subcategory and trends over time. The customer view highlights metrics such as total customers, sales per customer, and order distribution, with a ranking of top customers by profit and sales. This interactive dashboard enables users to switch between sales and customer insights, providing a comprehensive tool for optimizing business strategy and tracking performance against previous year benchmarks.

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Insurance Charges Prediction using Python

Developed a predictive model leveraging machine learning algorithms to estimate insurance charges based on customer demographics and attributes. The project involved data preprocessing, feature engineering, and model evaluation to enhance prediction accuracy.

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COVID-19 in India Dashboard in Tableau

This COVID-19 Dashboard for India provides a detailed analysis of the pandemic's impact across different states and demographics. Key metrics include total deaths by state, with Maharashtra showing the highest numbers, and confirmed, cured, and death trends over time. The dashboard also highlights age group breakdowns, with the majority of cases occurring in the 20-39 age range. Gender distribution reveals a higher infection rate among males (66.76%). Additional visualizations display statewise testing details, the number of ICMR testing labs, and doses administered by type (CoviShield, Covaxin, and Sputnik V). This dashboard offers critical insights into India's response to the pandemic.

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AirBNB NYC Dashboard in Tableau

This Airbnb NYC Dashboard provides insights into booking trends, pricing, and reviews across different neighborhoods. It includes key metrics such as total hosts, total neighborhoods, and average reviews per month, as well as visualizations like total bookings by neighborhood and room type. Manhattan and Brooklyn dominate the bookings, with average prices ranging from $87.50 (Bronx) to $196.88 (Manhattan). The dashboard also displays reviews per month by room type, with entire home/apt bookings having the most reviews. Mapping insights show the distribution of bookings across NYC boroughs. Additionally, a time trend graph captures review growth from 2011 to 2019, showing a sharp rise in 2019.

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Bike Sales Dashboard in Excel

Created an interactive dashboard that visualizes key factors influencing customer behavior in motorbike purchases. The dashboard provides actionable insights into customer demographics, preferences, and buying patterns, facilitating data-driven decision-making.

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HR Analytics Dashboard in PowerBi

Created an interactive HR analytics dashboard to visualize key employee metrics, including attrition rate, average salary, and years at the company. The dashboard breaks down attrition by age group, education field, and job role, offering insights into workforce demographics and satisfaction levels. It helps HR teams identify trends and make data-driven decisions to improve employee retention.

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Amazon Prime Video Dashboard in Power Bi

This Amazon Prime Video Dashboard provides comprehensive insights into the platform's content library, including key metrics such as the total number of titles (9,655), genres, ratings, and countries of origin. It visualizes the distribution of movies and TV shows, the genres with the highest number of titles (e.g., Drama with 986 titles), and age rating categories. The dashboard also features a world map showing content distribution by country, a breakdown of titles by release year, and a comparison of movies versus TV shows. This dashboard offers a clear overview for data-driven decisions about content trends on Prime Video.

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Telecom Churn using Python

Conducted an in-depth analysis of customer churn and its impact on revenue in the telecom industry. The project identified critical factors contributing to customer retention, using data analytics techniques to model and predict churn trends.

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Flight Ticket Prices Prediction using Python

Built a machine learning model to predict flight ticket prices based on various flight attributes. This project included data exploration, feature selection, and model optimization to accurately forecast ticket prices for better market analysis.

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Laptop Prices Prediction using Python

Developed a machine learning model to predict laptop prices based on specifications such as processor type, RAM, storage, and brand. The project focused on applying regression techniques and tuning models for high accuracy in price predictions.

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Housing Data Cleaning in SQL

Transformed raw housing data into a structured and analyzable format using SQL Server. The project involved data cleaning, normalization, and building a relational database schema to support efficient querying and analysis.

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COVID 19 Data Exploration

Utilized SQL Server to analyze global COVID-19 data, focusing on trends and key statistics like infection rates, recoveries, and fatalities. The project demonstrated expertise in SQL querying, data aggregation, and reporting.

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Movie Correlation with Python

Analyzed key factors influencing the gross revenue of movies, including budget, genre, and release date. The project involved data modeling and regression analysis to determine which variables had the most significant impact on box office performance.

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Education

MSc DATA ANALYTICS AND INFORMATION SYSTEMS MANAGEMENT (2023-2024)

Arden University | Berlin, Germany

• Acquiring expertise in Data Visualization fundamentals using R, and Python. MySql using SQL for databases. Proficient in Data Cleaning, Exploratory Data Analysis (EDA), Extract Transform Load (ETL) processes, and Machine Learning Algorithms. Skilled in PowerBI, Tableau, and Excel for effective data analysis and visualization.

• Utilizing Tableau for crafting interactive visualizations to highlight data trends effectively.

• Employing PowerBI to construct detailed reports and dynamic dashboards for comprehensive data analysis.

• Enhancing Excel proficiency for seamless data manipulation and visualization.

• Leveraging Python for real-world data cleaning, analysis, and machine learning implementation.

• Utilizing MySQL for structured data management and querying.

• Applying R for statistical analysis, visualization, and predictive modeling.

BACHELOR OF ENGINEERING IN ELECTRONICS AND TELECOMMUNICATION ENGINEERING (2016-2020)

Vidyalankar Institute of Technology | University of Mumbai

Mumbai, India

Experience

SOFTWARE DEVELOPER

Tata Consultancy Services (TCS) | Mumbai, India

Protean e-Gov (2020-2022)

• Engineered full-stack applications using the Java Spring Framework and SQL, delivering 20+ new features and enhancements that elevated system functionality and boosted user satisfaction.

• Architected and deployed APIs, integrating complex SQL queries to optimize data exchange, improving integration efficiency with third-party partners by 30%.

• Spearheaded enhancements in project workflows by introducing 5+ custom features, including automated email systems, feedback page development, and database integration.

• Streamlined data storage and retrieval with SQL, enhancing user experience and data management, reducing ticket volume by 40%.

• Resolved 100+ client-reported issues by diagnosing and optimizing SQL performance bottlenecks.

• Automated production deployment scripts, reducing deployment time by 70% and ensuring consistent, error-free application rollouts.

• Delivered maintenance and support, reducing system downtime by 25% and increasing system reliability.

• Conducted code reviews and provided mentorship to junior developers, ensuring adherence to best practices and high coding standards.

• Collaborated with cross-functional teams to identify and implement new client requirements, ensuring solutions were scalable and efficient.

• Aligned technical implementations with business objectives, delivering multiple client projects successfully within tight deadlines.

• Optimized application performance by refactoring existing code and enhancing SQL query efficiency, resulting in a 50% reduction in page load times and a smoother user experience.

• Led technical documentation efforts by creating comprehensive guides and API documentation, improving team onboarding, and facilitating knowledge transfer, which enhanced project continuity and reduced onboarding time by 35%.

SUMMER INTERNSHIP

Eduvance | Mumbai, India (2018)

Achieved an A+ grade in an intensive training and internship program by IBM, focused on Industrial Python. The program covered fundamental and advanced topics, including Python programming, error handling, web scraping, file operations, as well as data analysis and visualization using a variety of Python libraries and tools.

Contact Info

Email

anshutare@gmail.com

Phone

+49 1522 5247095

Location

Berlin, Germany

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