My on the amalgamation of sports and

My mother has always had a great impact on me and it was due to her influence that I got into data analytics. It so happened that she use to work for the Indian government’s census data collection team. It was while seeing her work on few of the assignments that she brought home, did I realize how the power of decisions based on data can trump instinct based decisions. Watching my mother enter numbers into the software that populated powerful visualization and then derive insights from them mesmerized me. Fascinated by how technology could impact lives I decided to pursue Computer Science and Engineering as my undergraduate major at Amity University.At Amity University, my rate of learning and knowledge grew at an exponential pace learning subjects such as Database Management Systems which taught me how I could store and manage data. I was always on the lookout on how I could blend my technical education with my interests in sports. The opportunity presented itself while interacting with my data communications professor. His research on the amalgamation of sports and data analytics to improve the way we played sports interested me. This idea clicked with me instantly and to learn the basics of data analysis I took up subjects like Data Communication and Computer Networks and Advanced Java Programming in my sophomore and junior year eventually pursuing my minor project under the guidance of my data communications professor. Under his guidance, I developed a statistical model to predict the probability of my favorite football team Manchester United winning a fixture. This prediction enabled us to calculate the total number of wins of the team for the season. Using freely available data sources like Wikipedia and openfootball, we extracted data for 10 seasons for all the teams Manchester United played with. Applying logistic regression on this data, we were able to develop a model to predict the outcome of future matches. This helped us determine the total matches they would win in a season. We tested our model on the 2011 season data and the model was able to correctly predict 70% of the wins for the season. This research further strengthened my interest in sports analytics.With the intent to blend sports with data analytics, I took Artificial Intelligence and Data Mining and Warehousing as my elective subjects which taught me the basics of problem-solving along with different data cleaning and data clustering techniques. These courses deepened my interest in the larger use of data analytics which led me to take up “Sportolysis” as my major(capstone) project in my senior year. Sportolysis was a tool which analyzed the performance of top 10 tennis players during the period of 2000-2012. The tool identified various factors like age, number of aces, matches won amongst others that contributed to the victory of each of the players. I collected data from various sources like ATP’s website, Kaggle and GitHub. After running data cleaning process using statistical programming language R, I used linear regression techniques to develop a model for each player, identifying key metrics that contributed each time a player won. The results were presented in the form of a business report in MS Excel highlighting the top 5 factors contributing to victory of each player. We were able to identify two important metrics: number of games saved and number of winners (winning shots). These two factors had significant contribution towards performance of players’ win with their individual contributions to a players performance varying. This project gave me a deep understanding of the applications of machine learning.         To further my interests, after graduation, I joined Fractal Analytics. My first project was with the Strategic Client Partnership team which was tasked with building an executive dashboard for the US team of Colgate Palmolive as my first project. With over ten reports to track simultaneously, decision making was a big challenge for our clients. My role in the project was to develop the complete functionality of the dashboard along with automating the data updating processes. The dashboard helped our clients track all the metrics at a single place instantaneously. As a result, data-driven decisions increased while the time taken to make these decisions decreased.While I did a few more projects on data visualization while also working with the product team on an in-house product, it was my ongoing projects with external clients that brought out the best in me. I was tasked with helping our client Kimberly Clark maximize their ROI / Volume by optimizing their advertising investments. I developed a predictive model using Ordinary Least Squares regression which helped us identify the individual impacts of marketing channels on volume sales. Using simulation and optimization techniques, we were able to recommend the optimum investment for various marketing channels. Our recommendations materialized into a sizeable increase in the ROI after the client implemented our recommendations. Together, these projects have given me rigorous exposure to MS-Excel, VBA, SQL, R and Qlikview as well exposed me to crucial insights on the US CPG and Retail industry.While working at Fractal for over three years, I have been exposed to various tools such as R, Python, and SQL and techniques such as Market Mix Modelling, Linear and Logistic Regression and Clustering which are widely used in analytics domain. Working extensively with our US-based clients gave me crucial insights on the US CPG and Retail industry. Although my professional experience has given me a snapshot of the skills used in analytics domain, I always wanted to pursue formal education in Analytics to sharpen my analytical and business skills. After three and a half years in analytics domain, I feel this is the appropriate time for me to take the next step in my career and learn advanced concepts of Analytics.  To advance my career in analytics, Master of Science in Analytics is the perfect course for me which will accelerate my career growth. Using advanced data analysis techniques that I will acquire during the Masters in Analytics program, my short-term goal would be to work with sports teams and companies such as Nike helping them in identifying opportunities, improving customer relationships and making strategic decisions by using advanced analytical tools and techniques. Additionally, I would like to explore how analytics could be used to integrate the abundance of new data and information into decision making processes of sports leaders.My long-term goal is to start a Sports Analytics venture with an aim to increase the probability of every successful decision that is being made on the sports field. Along with deepening the role of analytics in sports, I would like to take analytics to niche sports helping these sports realize the potential of analytics. With the power that analytics possesses, sportspersons could get much deeper insights of their own game and the opponent’s game, helping them train better. For the audience sitting at home and on the field, broadcasting interesting statistics as well as showing more real-time predictions would drastically improve their sports watching experience.My college and work experience has only helped me play until half time. To play to the final whistle, I require an engaging program that fosters industrially relevant skills. The Master of Science in Analytics at North Carolina State University is exactly that program that will help me finish the game. The fully integrated course that Institute of Advanced Analytics offers which combines the foundation of analytics with tools and techniques would provide me a holistic view of analytics domain. The courses on Customer Analytics along with Social Networks would help me identify crucial customer patterns. With Dr. Rappa whose has over 25 years of experience across various academic disciplines as the founding director along with other experts like professor Simmons, learning from these distinguished professors will make my time at university worthwhile.