5 ways big data will evolve in 2017

What to expect of big data in 2017

Scott Gnau, chief technology officer at Hortonworks, sees two key themes making an important impact on the growth and transformation of big data. First, data in real-time is transforming everything. Consumers are finding this to be true, and as IoT hits the mainstream, the trend towards real-time data will continue to explode upon practices involving big data. Second, for a variety of organizations, this will drive the need for connected data architectures to draw out value from raw material. The impact is already profound in every industry and will only grow larger this year.

Intelligent networks will lead to data clouds

The Internet of Things (IoT) and machine-to-machine connectivity are driving intelligent ecosystems where devices understand each other and work together in real-time, in the context of a larger need or purpose. This requires networks to expand and contract on demand, as well as messages to be routed and prioritized in real time. In this world, silos of data will be replaced by clouds of data. Freed from the need to conform to the rules of on-premise batch processing, intelligent self-configuring networks will emerge that can enable meaningful connections between devices. Crucially, these intelligent networks also provide the flexibility to enable new and faster delivery of data to the right place to be analyzed.

Artificial intelligence, real-time machine and deep learning and analytics at the edge will accelerate

It’s not uncommon for global enterprises to say they are going all cloud in the next decade to enable this change. So in 2017, “centralized-only” monolithic software and on-premise silos of data will truly start to disappear from the enterprise. Smart devices will collaborate and analyze what each other are saying. Real-time machine-learning algorithms within modern distributed data applications will come into play—they’ll be able to adjudicate “peer-to-peer” decisions in real time. Yet, data still has gravity; it’s still more expensive to move than store in relative terms. This will spur machine learning and analytics out at the edge, where the data was born and exists, in real-time, connected via the cloud.

Organizations will start to attempt pre-emptive analytics

So far, most data analytics have been post event and reactive. This will move to real-time and pre-event analysis and action. The unique value creation for organizations comes not just from processing and understanding transactions as they happen and then applying models, but by actually doing it before the patient, or the sensor, logs in to do something. Organizations will quickly move from post-event and even real-time to pre-emptive analytics that can drive activity instead of just modifying or optimizing them. This will have a transformative impact on the ability of data-centric organizations to identify new revenue streams, save costs and improve their customer intimacy.

Connected modern data applications will rise in importance

The notion of being able to connect data-at-rest and data-in-motion in different data platforms, across multiple cloud providers and on premise with true application portability, is the central differentiator between the future of data vs. the past. For organizations to succeed with data, apps and data need to be connected via a platform or framework. This is the foundation for the modern data application in 2017. Modern data applications are highly portable, containerized and connected. They will quickly replace vertically integrated monolithic software.

Data will be everyone’s product

In this new world, your data also becomes a product to be bought and sold. Software can be replaced; your data is irreplaceable and has value. Consumers until now have largely given away the value of their purchasing power on social media and online commerce, but they will become increasingly savvy about how and whether they do this. So whether you are a healthcare organization or an individual consumer, your data will become a product with value to buy, sell or lose. There will be new ways, new business models and new companies looking at how to monetize that asset. This means, you’d better start thinking how data is a product for your organization in 2017, if you aren’t already.