January 10, 2018

2018 Trends & Predictions for Enterprise Data

Infrastructure technology made significant advancements in 2017, but expect to see that technology drive big new changes in the coming year:

Data is the new currency of digital business.

Forget about Bitcoin and Cryptocurrencies – in 2018, data is the loot that will propel your business. This is hardly a new concept, but industry leaders are quickly figuring out how to monetize, capture, create value from, and take action on data. Not only will the volume of data continue to explode, but the means of gathering data (sensors and other data collectors) will become much more efficient. As entire data ecosystems develop, the need for lightning fast processing and massive storage capacity will increase dramatically. And, as the value hidden within these active data sets begins to materialize, the winners will be those who can extract data’s value to deliver the most powerful business outcomes.

Artificial Intelligence, Machine Learning and Cognitive Systems will disrupt infrastructure architectures.

Machine learning is a technical discipline that extracts knowledge and patterns from a series of observations and relies solely on data for training of these systems. These observations can be supervised (observations contain input/output pairs), unsupervised or reinforced. Regardless of the method used, each relies upon an ability to quickly process and utilize this machine data. For these AI/ML systems, the massive amount of data being ingested from sensors and systems everywhere will create performance issues. ML systems function properly with active data loops: extract, learn, act, reinforce. If the data infrastructure is overwhelmed or bottlenecked, this loop breaks down. This phenomenon is already affecting traditional databases today and this impact will be magnified with machine learning systems. Learn the 5 reasons why current all-flash arrays are off-target in this webcast with George Crump from Storage Switzerland.

Compute processing and analytics will accelerate its shift to the edge.

Currently, significant data processing and evaluation occurs in centralized locations where data can be stored, referenced, and utilized. This centralization, however, means that real-time data utilization can’t be implemented on the front-lines of consumer interactions. Consider Walmart, for example – they have tens of thousands of locations, but only a handful of centralized data processors. This separation prevents valuable real-time consumer data (what are your buying patterns? What aisles were you shopping on?) from having a point-of-sale impact (“here is a coupon suited to your interests”). This year, you will continue to see a shift of processing away from centralized data centers and toward the edge, empowering individual service locations to provide highly personalized, data-rich experiences for consumers.

IoT will force many to rethink their data architectures.

In 2018, the Internet of Things will implement cross-channel devices that generate massive amounts of data, stressing existing compute systems to the breaking point. As these systems grow, the performance demands will increase to the point where it’s no longer economically feasible to run on legacy architectures. This will manifest itself initially as increased network costs, but this will also require the use of faster and more effective compute and storage resources to alleviate these data-centric pain points.

Expect more consolidation in the industry.

As the need for greater power and flexibility increases, expect to see more partnerships, mergers and acquisitions as the players align themselves to tackle the challenges described above. The open-source big data vendors may be the first to consolidate, to give them a stronger competitive edge against the larger, established vendors. As SSD-based storage solutions continue to utilize NVMe, cost points will erode and customers will move more workloads away from mechanical spinning drives forever. Technological advancements such as 3D Xpoint will find a place in the data center, provide better I/O performance and the ability to support the greater throughput that will be needed for cognitive systems and analytics. Adoption of these solid state technologies will force greater infrastructure alliances and eventually consolidation as larger vendors, struggling to innovate, will use M&A as an extension of their core R&D.

2018 will be an exciting year for the Cloud and data center industries, as technologies supporting Artificial Intelligence, Machine Learning, and the Internet of Things will harness data to achieve growth across industries and sectors. At Vexata, we’ve got a number of projects in 2018 that will show how the Vexata architecture unlocks the potential of data in your enterprise. To get a better understanding of how the Vexata architecture overcomes the 5 key shortcomings of all-flash arrays, join us on Jan 18th for this webcast.

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