Over the years, data-driven companies have followed four primary principles to democratize data access: 1) Migration to the Cloud, 2) Scalability, 3) Flexibility & Agility and 4) Availability.
These four principles have shaped the evolution of data analytics and data infrastructure: from the pre-2015 co-location of storage and compute in purely monolithic architectures, to the 2015-2020 separation of compute and storage in cloud data warehouses, and—finally—to today’s post-2020 separation of data and compute in data architectures.
Data now exists as its own, separate tier – built on open source standards and formats. The Data Tier brings data warehousing capabilities to the data lake and enables net-new capabilities that data warehouses cannot provide. It makes data highly accessible and flexible across multiple tools and engines and in general, makes data analytics and data architectures much more effective at meeting business requirements and providing business value, while at the same time being affordable, cost effective and operationally effective.
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