What does 2016 have in store for Big Data?

The dying 2015 was a big year for big data, and 2016 is set to be even bigger. As the year comes to a close, various predictions are being made over what will next year bring.

Among those giving their predictions is Prat Moghe founder and CEO of big data firm Cazena. According to Moghe, CIOs are about to get their “mojo” back next year, and workload intelligence for cloud infrastructure, together with best-of-breed technologies will become the new query optimisation.

According to Moghe, CIOs spent decades mastering and building enterprise IT infrastructure. But the arrival of cloud services, and their subsequent rapid adoption by employees impatient with the old paradigm’s lack of speed and convenience, left them playing catch-up as shadow IT took root.

In 2016, CIOs will take advantage of enterprise-ready cloud services to become brokers of cloud services that meet IT mandates for governance, compliance and security as well as business needs for agility and responsiveness. Cloud integrations with existing data sources will allow CIOs to offer a satisfactory user experience for employees, which will play a critical role in dramatically reducing IT circumvention.

A new category of value-added data services is expected next year, on top of the public cloud. Named “database platform-as-a-service” by Gartner and “big data processing as a service” by Forrester, it will make major headway now that vendors address data movement, security and other early barriers through end-to-end automation and controls.

These services will drive a shift in focus from individual database technologies, such as Hadoop or MPP SQL, to platforms that offer a number of these workload engines in order to provide the best cost and performance across disparate data types and use cases. The responsibility of choosing and applying the appropriate technology for specific types of analysis will no longer rest with the enterprise, but instead be automated by these services.

As such, cloud-computing solutions such as Hadoop as-a-Service, Spark-as-a Service and Data Warehouse-as-a-Service will consolidate as Big Data-as-a-Service.