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SUBMISSION INSTRUCTIONSThe Universal Data Model (UDM) is an abstract data model that is designed to capture, clean, integrate,and deliver all insights in simple, flexible, and powerful ways. The UDM allows our wide range clients to accelerate delivery of big data analytics with speed and accuracy thanks to the combined power of a flexible, automated data model and Alteryx Server. Accenture has successfully implemented the UDM in clients across a wide range of industries including Telecommunications, Mining and Retail. Of note Alteryx is at the heart of Accenture’s Sports Analytics Platform being developed in conjunction with a variety of our sporting organisations including Rugby Australia (RA).
Working with coaches, such as Wallabies coach Michael Cheika, and the High Performance Team, Accenture has built a bespoke tool, powered by Alteryx, that will give coaches and players a 360° analysis of their on-field and off-field performance metrics including wellness, biometrics, injuries, training load and detailed play-by-play stats.
The UDM and associated sports analytics platform has been developed making use of Alteryx Designer and Alteryx Server to deliver streamlined, repeatable solutions. The UDM is made up of 31 unique macros that handle all aspects of data loading, data cleansing, platform operations, advanced analytics, and auditing. The platform can automatically create feature sets, dimensional models, or data extracts to meet all business needs.
The platform makes use of Amazon S3 and Redshift and deliveries a single view of player, teams and competitors to support all business needs including visualization, reporting, advanced analytics and mobile apps across different data velocities.
Thanks to Alteryx, the UDM and Sports Platform has become highly extensible allowing clients to customize the solution based on their architecture and existing software tools:
The platform makes use of the full range of Alteryx capabilities across data preparation, spatial, in-database, data investigation and predictive.
Parameters drive different behaviors and output for each macro. For example below is a Supertype Load macro that will have different outcomes depending if data input has attributes, spatial, time-series or binary large objects.
For Rugby Australia, the platform has grown at an exponential rate over the last 12 months, capturing every aspect of Rugby played anywhere in the world. Currently the platform has:
We are now taking the platform to the next level developing sophisticated predictive, machine learning and deep learning models to help improve the performance of Australian athletes and teams on and off field. This has seen the platform expand to include a range of new features including:
Below are some of the benefits our clients are seeing making use of our platform.
Specifically, for Rugby Australia, we have seen the following benefits:
Related Resources:
External website showing the work Accenture has done with Rugby Australia: Link
Ad campaign talking about the work done at Rugby Australia: Link
Blog post on Sports Analytics: Link