Jason Hoffman, CTO of Joyent, predicts that the future of big data will be about the convergence of data, computing and networks. The PC was the convergence of the computing and networks, while the convergence of computing and data will enable analysis performed directly on Exabytes of raw data enabling ad hoc questions to be asked on extremely large data sets.
Artificial intelligence that will match human intelligence will allow us to ask questions and finding answers more easily by simply asking natural questions to computers. Already Japanese scientists have built a super-computer that mimic the brain cell network and reached 1% of brain capacity. To achieve this that simulated a network consisting of 1.73 billion nerve cells connected by 10.4 trillion synapses. The process took 40 minutes, to complete the simulation of 1 second of neuronal network activity in real, biological, time. In the coming years these super-computers will become the standard. At the moment, users still need to know what you want to know, but in a future with such super-computers it is all about the things that you don’t know.
The real benefits will be when organizations do not have to ask questions anymore to obtain answers, but simply find the answer to question they never could have thought of. Advanced pattern discovery and categorization of patters will enable algorithms to perform the decision making for organizations. Extensive and beautiful visualizations will become more important and help organizations understand the brontobytes of data.
Big data scientists will be in very high-demand in the coming decades, as McKinsey also predicted in 2011 already. The real winners in the big data startup field however, will be those companies that can make big data so easy to understand, implement and use that big data scientists are not necessary anymore. Large corporations will always employ big data scientists, but the much large market of Small and Medium sized Enterprises do not have the money to hire expensive big data scientists or analysts. Those big data startups that enable big data for SME’s without the need to hire big data experts will have a huge competitive advantage.
The algorithms developed by those big data startups will become ever smarter, smartphones will become better and in the future anyone will have a supercomputer in its pocket that can perform daunting computing tasks in real-time and visualize it on the small screen in your hand. And with the Internet of Things and trillions of sensors, the amount of data that needs to be processed by these devices will grow exponentially.
Big data will only becomes bigger and brontobytes will become common language in the boardroom. Fortunately, data storage will also become more widely available as well as cheaper in order to cope with the vast amount of data. Brontobytes of data will become so common in boardrooms, that eventually the term big data will disappear again and big data will become just data again.
However, before we have reached that stage, the growing amount of data that is processed by companies and governments will create a privacy concern. Those organizations that stick to the ethical guidelines will survive, other organizations that will take privacy lighthearted will disappear, as privacy will be self-regulating. The problem will be however with the governments as citizens cannot simply move away from their government. Large public debates about the effects of big data on consumer privacy will be inevitable and together we have to ensure that we do not end-up in Minority Report 2.0 or in a ‘1984-setting’.
The future of big data is still unsure, as the big data era is still unfolding, but it is clear that the changes ahead of us will transform organizations and societies. Big data is here to stay and organizations will have to adapt to the new paradigm. Organization might be able to postpone their big data strategy a little bit, but we have seen that organizations that already have implemented a big data strategy, do outperform their peers. Therefore, start developing your big data strategy, as there is no time to waste if your organization also wants to provide products and services in the upcoming big data era.