Big Data is Getting Bigger.

 

As Co-Chair of the Analytics & Big Data Committee in SNIA, I am constantly looking at how big data is morphing into an epidemic of massive data growth and it's intriguing to me what is contributing to this growth and how.  Explosive data growth is a reality and the trajectory is continuing to be strong.  In order to accommodate and support this level of intensification, more robust and powerful data management solutions are becoming more important than ever before. Data generation and the diversification of data use drive the adoption of more role-based storage solutions within the data center.  These factors, coupled with the transition to highly virtualized data center environments, affects how organizations buy and manage server, storage, and network assets and are key drivers in what is propelling Big Data into an everyday reality.  The outlook is Big Data in the Cloud.

 

Big Data is comprised of datasets that grow so large that they become cumbersome to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing. The growth trend continues because of the benefits of working with larger and larger datasets that allow analysts to discover business trends and solve problems. Though a moving target, current limits are on the order of terabytes, exabytes and zetabytes of data.  Data is everywhere, whether it is from users, applications, or machines and it’s growing exponentially with no vertical or industry being spared.  Due to this reality, IT organizations everywhere are forced to come to grips with storing, managing and extracting value from every piece of it -– as inexpensively as possible.  This begins the real race to cloud computing where the framework needs the ability to process data increasingly in real-time and in greater orders of magnitude -– and at a fraction of what it would typically cost.

 

Storage providers, such as NetApp, play a huge role in the explosive data growth and increase in scale.  After all, they store the data and they need to be able to provide a robust enough environment and solution offering to accommodate such datasets.  The most effective solutions are ones that efficiently process, analyze, manage, and access data at scale. Specifically, solution portfolios that are organized by the primary use cases of analytics, bandwidth, and content are ones that cover the key bases for success.

 

Analytics for extremely large data sets focus on providing efficient analytics for those datasets that are significantly larger than any we’ve been accustomed to in the past.  Analytics is all about gaining insight, taking advantage of the digital universe, and turning data into high-quality information, providing deeper insights about the business to enable better decisions.

 

Bandwidth is related to the performance for data-intensive workloads.  High-bandwidth applications include high-performance computing and the ability to perform complex analyses at extremely high speeds. They also include high-performance video streaming for surveillance and mission planning as well as video editing and play-out in media and entertainment

 

Finally, content focuses on the need to provide boundless secure scalable data storage. Content solutions must enable storing virtually unlimited amounts of data, so that enterprises can store as much data as they want, find it when they need it.  The simple ABC's of Big Data.