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A76ers’ Data Intelligence SLAM-DUNK
Technology Category
- Analytics & Modeling - Big Data Analytics
Applicable Functions
- Sales & Marketing
- Business Operation
Services
- Data Science Services
- System Integration
The Challenge
The Philadelphia 76ers, a part of Harris Blitzer Sports & Entertainment’s (HBSE) portfolio, had a data ecosystem consisting of over 130 data sources. Managing and expanding this data infrastructure was becoming increasingly difficult and time-consuming. The process of connecting to a new data source could take weeks, severely limiting the bandwidth of the data team. The fixed timelines surrounding live events made flexibility and agility of data operations paramount. The existing data consolidation procedure was not scalable and was preventing the team from fully focusing on uncovering the insights the data could provide.
About The Customer
Harris Blitzer Sports & Entertainment (HBSE) is a leading sports and entertainment company. Its portfolio includes premier brands, venues, and franchises, centered around three marquee assets: the NBA’s Philadelphia 76ers, the NHL’s New Jersey Devils, and the Prudential Center in Newark, NJ. HBSE is also actively engaged in areas of esports and sports technology. The Philadelphia 76ers are the marque sports franchise in HBSE’s portfolio. They use an extraordinarily diverse range of data sources- from online advertising platforms, through ticketing systems, to audience engagement data, which all need to be integrated.
The Solution
To overcome these challenges, the Data and Analytics team at HBSE was looking for a solution that would act as a hub for their rapidly expanding data lake, and give them the ability to quickly plug-and-play to new data sources. They use a Snowflake data warehouse infrastructure to store data fetched with Adverity, which is then harmonized before being sent to Tableau for reporting. By placing the Adverity platform at the forefront of their complex data infrastructure, the data team at HBSE was able to automate and accelerate their data operations. The data now flows automatically into the centralized data warehouse, and the team doesn’t need to spend any additional time and effort on consolidating and harmonizing it.
Operational Impact
Quantitative Benefit
