How Data-Focused Executives are Using Columnar, Massive Parallel Processing and In-Memory Storage to Deliver High Performance Analytics Solutions
Data storage is often seen as a cost to be minimized. But for enterprises that want to harness data to create
faster, more efficient business models, the data infrastructure they choose can make or break their BI and data-driven transformation initiatives.
Based on in-depth interviews with six executives in Corinium’s global network, this special report highlights how high-performance data infrastructures are helping data-focused leaders drive greater ROI and transform their organizations in 2021 and beyond.
Our research highlights why conventional relational databases or cloud-based data storage may not be fast enough for certain advanced analytics projects. This includes those that need fast upload speeds, fast insight delivery or fully automated analytics self-service capabilities.
We identify three high-performance technologies that companies including MoneySuperMarket, The Gym Group and Piedmont Healthcare are exploring to upgrade their data infrastructure.
Then, we take an in-depth look at why pizza giant Domino’s is putting in-memory processing at the heart of its analytics ecosystem, to enable real-time analytics on huge volumes of operational and third-party data.
Our findings look at how enterprises can integrate high-performance solutions with their existing data infrastructure – whether they want to improve the performance of a legacy data warehouse, unify multiple BI systems with a single high-performance access layer or totally replace a legacy data store.
We conclude that starting the journey by adding a ‘bolt-on’ high-performance layer onto an existing data infrastructure may be a convenient way for some to reduce database query times and enable ad hoc analytics quickly, without having to reimagine their entire ecosystems.
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