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Browse: Abstracts, Winners and runners up, Awards Ceremony (Watch Recording / View Slides), Posters by HPCC Systems InternsPosters by Academic Partners, Poster Judges, Virtual Judging, Home

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Christopher Connelly is a Data Scientist at North Carolina State University, who works with various sports teams to help them discover insights into the data collected about their players, that may help them to improve their fitness and technique. In previous years, he worked on the Athlete 360 project at NCSU and HPCC Systems supported this research via our Academic Program. Chris joined the HPCC Systems Intern Program in 2019 when he collected GPS data from the men and women's soccer teams to carry out data analytics. In 2021, his intern project switched focused to looking at data collected from the women's basketball team. The aim was to use HPCC Systems to clean and analyse the data and provide visualisations in a dashboard via RealBi. In the past, Chris has used our bare metal platform, but in 2021, he was an early adopter of our Cloud Native platform providing valuable feedback to the development team.

As well as the resources included here, read Chris's intern blog journal which includes a more in depth look of his work during his 2021 internship. To learn more about Chris's previous intern project success, view the poster Chris entered into our 2019 Poster Contest

Poster Abstract

In the past NC State Strength and Conditioning has worked with HPCC Systems to create solutions for taking different data streams and bringing them together for a comprehensive analysis to improve athlete wellbeing and performance.  Here you will see some solutions using HPCC Systems and RealBI to provide insight from data collected with the NC State Women's basketball team. You will see some differences from working with a Bare Metal environment to a Kubernetes environment. From uploading data into a cloud based environment, to visualizing the data in a streamlined and interactive dashboard, see how these solutions can help our understanding of this data to provide better service to these student athletes.

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