Jay Subramanian, VP, ONTAP Product Management
It’s clear Big Data Analytics drives profitability and is becoming essential to the success of enterprises. Unfortunately, first generation, share-nothing analytics platforms are not sufficient to meet the security, reliability, scalability or performance requirements of business-critical applications. They lack fundamental capabilities necessary to protect critical data, drive costs down, and provide the flexibility needed to meet evolving needs.
First generation Big Data Analytics platforms are built around clusters of individual computer platforms with internal direct-attached storage (DAS), but this architecture is inherently problematic and non-scalable. Component failure, particularly DAS, can cause the analytics’ process to fail or drastically slow down. There is no convenient way to back up the data and quickly restore it, nor any way to manage the data lifecycle as analytics become core to the enterprise and the datasets grow exponentially. It is difficult to scale compute and storage elements independently, or even at all. In this webcast learn how a second generation Big Data Analytics platform addresses and overcomes these challenges.
This new, highly scalable analytics approach provides far more flexibility, and effortlessly leverages the cloud in combination with on-premises resources. Compute and storage infrastructure can be scaled independently – driven only by current requirements. Analytics applications can now efficiently access data directly from existing enterprise storage systems, eliminating unnecessary replication of data. See how a second generation big data analytics platform can reduce server, storage, and software license costs by optimizing resource utilization, and provide all the data security, scalability, performance, and analytics capability required by your enterprise.