Data/Business Analyst

Austin Mathew • Peerlist

This project explores and analyzes Netflix’s global content library using Python. I performed data cleaning, exploratory data analysis (EDA), and created insightful visualizations to uncover trends in content distribution, release patterns, ratings, and contributors.The project answers questions like:<ul><li>How is Netflix’s content split between Movies and TV Shows?</li><li>Which years saw the highest content additions?</li><li>How are content ratings distributed?</li><li>Who are the most frequent directors and actors featured on Netflix?</li></ul>Using libraries such as Pandas, Matplotlib, and Seaborn, the analysis uncovers meaningful patterns in Netflix’s global streaming catalog, delivering visualizations and summaries that simplify complex data for better understanding.

Netflix Data Analysis Project

🚀 Enhancing Business Decisions with the Zomato Analytics Dashboard 📊Excited to share my latest project: The Zomato Analytics Dashboard, designed to provide deep insights into food delivery performance, restaurant reviews, and customer preferences.Business ProblemZomato stakeholders needed a data-driven approach to optimize delivery operations, track restaurant performance, and improve customer satisfaction. The challenge was to create a scalable, real-time dashboard that provides actionable insights.Requirements &amp; Data Analysis🔹 Integrated multiple datasets, including orders, restaurant details, and customer reviews.🔹 Defined key KPIs like Total Orders, Average Delivery Time, Order Value, and Ratings.🔹 Applied filters for city-wise trends, cuisine preferences, and discount utilization.🔹 Used charts and visualizations to track order trends, top restaurants, and delivery efficiency.Tools &amp; Techniques Used✅ Power BI – for real-time interactive visualizations.✅ SQL – for efficient data extraction and transformation.✅ DAX – for advanced data calculations and KPI tracking.✅ Data Validation – to ensure accuracy and consistency in reporting.Outcomes📈 Improved visibility into operational bottlenecks.📉 Reduced average delivery time with data-driven optimizations.🎯 Better marketing strategies based on customer behavior insights.This project reinforced my passion for data analytics and business intelligence. Always excited to solve real-world problems with data!

Zomato Power Bi Dashboard

The project involved organizing and analyzing data from multiple sources, including SQL Server databases containing employee details, salary information, department budgets, and project timelines. This structured approach enabled the dashboard to highlight key metrics such as departments and projects over budget, performance trends, and budget allocation vs. expenditure analysis over a two-year cycle.This robust solution empowers organizations to leverage SQL Server’s data processing capabilities and Power BI’s visualization strengths to identify risks proactively, optimize resources, and enhance decision-making.

Transforming Workforce and Budget Management

Data Analytics professional at Schenider Electric having 2+ years of experience with Excel,SQL, Python,Tableau

This project contains the data record of all types of crime against women in India in the span of 2001-2014.The objective of this project is to compile data encompassing various forms of crimes against women in India spanning from 2001 to 2014, with the primary goal of shedding light on the status of women in our society and emphasizing the importance of addressing this issue.

Crime Against Women 2001-2014

This project report seeks to assess the performance of businesses featured on the 2019 INC 5000 list. The provided dataset encompasses details such as industry, establishment year, website, location, 2019 revenue, growth rate, employee fluctuations, and years of list inclusion for each company.

Analysis of INC 5000 Companies

This data analysis aims to uncover insights about mobile apps' future business strategies and development approaches. It summarizes findings from historical data sourced from the google playstore, spanning from June 2012 to February 2019. The study also sheds light on trends related to mobile app categories, usability, and user expectations.

Mobile Apps Playstore Data Analysis

According to data on monthly pizza sales, there are seasonal variations in sales, with some months having lower sales than others. The project may explore possible causes of these variations, such as seasonal factors, promotional activity, or modifications in consumer behavior.The breakdown of pizza sales during the morning, afternoon, and evening hours is seen in the data on sales by time of day. The project could study how this breakdown differs by category and whether there are chances to boost sales at particular times of the year.Last but not least, information on pizza sales by category offers insight on the most well-liked pizza varieties among consumers. The project might look into customer demographics, pizza preference patterns, and possible markets for fresh pizza selections.The overall goal of the Pizza Sales Project seems to be to better understand pizza sales trends and locate chances to increase sales through the use of data analysis. The project may include suggestions for marketing and promotion plans, adjustments to the menu, or other techniques designed to boost sales and promote business expansion.