Streaming Real-Time Sporting Analytics for World Table Tennis

Reimagining a data architecture to provide real-time data flow for sporting events can be complicated, especially for organizations with as much data as World Table Tennis (WTT). Vatsan Rama (Director of IT, ITTF Group) shares why real-time data is essential in the sporting world and how his team reengineered their data system in 18 months, moving from a solely on-premises infrastructure to a cloud-native data system that uses Confluent Cloud with Apache Kafka® as its central nervous system. World Table Tennis is a business created by the International Table Tennis Federation (ITTF) to manage the official professional Table Tennis series of events and its commercial rights. World Table Tennis is also leading the sport digital transformation and commercializes its software application for real-time event scoring worldwide. Previously, ITTF scoring was processed manually with a desktop-based, on-venue results system (OVR) —an on-premises solution to process match data that calculated rankings and records, then sent event information to other systems, such as scoreboards.  To provide match status in real-time, which makes the sport more engaging for fans and adds a competitive edge for players, Vatsan reengineered their OVR system to allow instant data sync between on-premises competition systems with the Cloud. The redesign started by establishing an event-driven architecture with Kafka that consolidates all legacy data sources, including records in Excel along with some handwritten forms (some dating back 90 years, even including records from the 1930 World Championship). To reduce operational overhead and maintenance, the team decided to stream data through fully managed Kafka as a service on Azure, for a scalable, distributed infrastructure. Vatsan shares that multiple table tennis events can run in parallel globally, and every time an umpire marks scores in a table, the data moves from the venue into Confluent Cloud, and then the score and rankings are sent to betting organizations and individuals on their mobile apps. EPISODE LINKSEvent Processing ApplicationFully Managed Apache Kafka on AzureWatch the video version of this podcastKris Jenkins’ TwitterStreaming Audio Playlist Join the Confluent CommunityLearn more with Kafka tutorials, resources, and guides at Confluent DeveloperLive demo: Intro to Event-Driven Microservices with ConfluentUse PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)  

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Streaming Audio features all things Apache Kafka®, Confluent, real-time data, and the cloud. We cover frequently asked questions, best practices, and use cases from the Kafka community—from Kafka connectors and distributed systems, to data mesh, data integration, modern data architectures, and data mesh built with Confluent and cloud Kafka as a service. Join our hosts as they stream through a series of interviews, stories, and use cases with guests from the data streaming industry. Apache®️, Apache Kafka, Kafka, and the Kafka logo are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by The Apache Software Foundation is implied by the use of these marks.