The Larry H Miller Group of Companies includes auto dealerships, a finance and insurance company, and Larry H Miller Sports and Entertainment. LHMSE owns the Megaplex movie theatres, basketball teams Utah Jazz and Salt Lake Stars, baseball team Salt Lake Bees, a sports talk radio station, an arena venue and the Tour of Utah cycle race.
Even the casual observer can see there is a diversity of data sources running into these companies. This poses a challenge for Dustin Spangler, VP of data and analytics at LHMSE and his primary development team of five people.
One is the elusive single customer view and customer identification. A corporation might buy several tickets for a basketball game and therefore be the customer, while the employees of that corporation would be the attendees. “Defining that customer path for each entity is slightly different, so that’s been a challenge for us. Another is that we want to understand who our customer is across multiple platforms and multiple entities, whether they go through the app or buy a ticket through a third party site.”
This is a particularly tricky issue with the Utah Jazz basketball games. LHMSE ticketing goes through Ticketmaster but fans can also buy through the NBA website which has a Utah Jazz subdomain, resulting in duplicate tracking systems.
They are currently using Teradata Vantage as their data platform and leveraging WhereScape RED as their ETL tool, as well as using Python and R. Wherescape allows his team to have much greater impact relative to the size. “It enables us to do automation and templating of our processes that makes it so that with a small team, we can work rapidly and compete with teams ten times our size in terms of volume and quality of work,” he said.
The decision to go with those tools was made three years ago. Spangler said: “We wanted to focus on the analytics over engineering. We wanted to use tools and applications that made it easy for us to just go as quickly as possible as opposed to having to write a lot of code.”
The choice of Teradata was not made lightly and came after a thorough assessment and evaluation process. His company was in the midst of a drive to move to the cloud and shortlisted three cloud vendor platforms, Google Cloud, Snowflake and Teradata, to test out.
The conditions were that they spend two weeks using each one, with one developer in charge, no early access to the data and at the end, the labour hours for the project would be reported. Essentially they wanted to see which platform would be least labour-intensive and therefore make the team most efficient.
The platforms were evaluated on: ease of use, tool integration, machine learning/artificial intelligence capabilities, maintainability, database administration, data ingestion, features and roadmap. For each criteria, the platforms were scored from one to five with Spangler joking that one meant non-existent while five meant the cyborgs were taking over.
After the evaluations, Spangler and his team concluded that all of the platforms could succeed with the right resources in terms of people, software and hardware/CPU and most of the scores given were twos, threes or fours. They also concluded that the total cost of ownership was about the speed to insights/capabilities, the analytic and reporting platform, the ability to analyse data where it lies, workload management and security.
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