Optimizing Data Optimizes Theme Park’s Visitor Experience
January 31, 2022
With locations across the globe, this major theme park company offers fun and entertainment for families of all ages.
What’s Going On?
A major theme park (MTP) decided to undertake the enormous challenge of customizing its guests’ experiences. Their goal was to enable parents to get as much joy and laughter as their kids – while also enjoying some well-deserved relaxation and rejuvenation. Collecting and analyzing the massive amounts of data associated with custom-designing the experiences of individual visitors requires a well-orchestrated digital infrastructure. MTP asked Prolifics to take a hard look at the database and analytics platforms the theme park was currently using. The objective was to see if MTP was getting adequate ROI – and how they could further optimize performance.
What Prolifics Did
Prolifics examined MTP’s current infrastructure and pinpointed specific ways for them to get more while spending less.
MTP had been using Teradata, which consists of a massive box of tools. Teradata, for many businesses, is a central repository of data and data management processes. It’s used for standard reporting, business intelligence, and advanced analytics. MTP was also using Business Objects, and SAS was their platform of choice for business analytics.
Prolifics’ analysis revealed that MTP was underutilizing Teradata—despite its high cost—and doing all of their heavy-lifting in Business Objects and SAS. As a result, Teradata was doing little to no heavy lifting while consuming considerable funds.
On the other hand, the Business Objects platform was handling the majority of their data work. Consequently, Business Objects was costing MTP more and more money because it had to handle the bulk of the workload, while Teradata wasn’t being leveraged for that work at all. SAS was doing something similar – pulling in all the data they needed for what they wanted to do, resulting in exorbitant SAS licensing fees.
So even though MTP had invested significant funds in Teradata, they were, essentially, only using it as a passive data repository.
Prolifics’ next move was to ensure MTP was getting the most out of their investments by balancing the workload among Teradata, Business Objects, and SAS.
Prolifics reengineered the infrastructure in a way that allowed Teradata to do more work, reducing the workload performed in Business Objects. In this way, MTP would see a better return on their investment in Teradata and no longer have to build out their Business Objects hardware in perpetuity.
The Results: Prolifics Optimizes MTP’s Investments
Using our analysis to identify how MTP was using Teradata, SAS, and Business Objects, Prolifics was able to explain how to balance the data workload and optimize MTP’s investments.
Naturally, MTP wanted to see proof of the efficacy of Prolifics’ solution, so Prolifics showed them:
- How the flow of SQL data between platforms was optimized
- An advanced SAS algorithm being run within Teradata, allowing SAS to only pull in the resultant sets it needed to do its work
The theme park then implemented Prolifics’ recommendations. As a result, they saved $1 million on SAS licensing alone, in addition to other bottom-line benefits.
To learn more about what Prolifics can do for you, connect with an expert today.
Prolifics is a global digital transformation leader with expertise in Data & AI, Integration & Applications, Business Automation, DevXOps, Test Automation, and Cybersecurity across multiple industries. We provide consulting, engineering and managed services for all our practice areas at any point our clients need them. Vision to Value. Faster. It’s not just the Prolifics’ tagline, it’s what drives us. Reach out to learn more – firstname.lastname@example.org.Download Case Study ;
A Theme Park's Latest Ride: Optimizing Data Management
Download this case study for more details on:
the theme park’s challenges and how Prolifics met them;
how Prolifics optimizes the theme park’s investments by reengineering infrastructure and balancing workloads.