Big Data and Big Data analytics has come a long way in recent years, and 2017 is promising even greater interest and opportunity. With the Internet of Things playing a significant role in the expansion of Big Data along with cloud tools, chatbots and SaaS services providing greater access, storage and usage possibilities, the experts believe Big Data will play a role in encouraging the development of augmented reality products that use collected information to influence our behaviors, the power of deep learning will move from theory to reality, and businesses will continue attempts to better integrate Big Data into operations while preserving, if not bolstering, security.
Those in the know believe that artificial intelligence (AI), encompassing deep learning, will continue to trend in 2017, building on Big Data and the many profits we’ve already gained from Big Data analytics. Recently, deep learning has stolen the spotlight with notable accomplishments in machine translation and image recognition, with companies and investors are taking note. Suggests Bill Franks, Chief Analytics Officer of Teradata, “Deep learning will move out of the hype zone and into reality.” Franks does, however, advocate prudence, “Deep learning is getting massive buzz recently. Unfortunately, many people are once again making the mistake of thinking that deep learning is a magic, cure-all bullet for all things analytics. The fact is that deep learning is amazingly powerful for some areas such as image recognition. However, that doesn’t mean it can apply everywhere. While deep learning will be in place at a large number of companies in the coming year, the market will start to recognize where it really makes sense and where it does not. By better defining where deep learning plays, it will increase focus on the right areas and speed the delivery of value.”
As new data generation devices are implemented, Big Data plays an even more significant role in AI and says Quentin Gallivan, CEO of Pentaho, “The early adopters of AI and machine learning in analytics will gain a huge first-mover advantage in the digitalization of business… because they know that the sooner these systems begin learning about the contexts in which they operate, the sooner they will get to work mining data to make increasingly accurate predictions.” Such usage of Big Data alongside AI could ensure a range of benefits from improved customer recommendations, to better check-out scanning and inventory tracking, to enhanced security measures that better protect individuals, businesses, and governments.
Experts predict the new year will see Big Data applications that speed up analytics and make the entire realm of Big Data more accessible. It’s likely we’ll see an upsurge in platforms able to integrate data from multiple sources, an undertaking encouraged by organizations eager to better utilize their vaults of data more quickly and efficiently. According to Gallivan, 2017 will see the evolution of Big Data and IoT systems able to help organizations prosper through self-service data prep, embedded analytics, automated data onboarding, business digitization, and cyber security scrutiny.
Moreover, the popularity of hybrid and cloud services will work hand in hand with Big Data advances as data storage and analytics converges into smarter systems. It’s suggested by some that more businesses will run their APIs in the cloud, further augmenting the cloud’s scalability with elasticity that’s better able to manage demand spikes and promising faster innovation and adoption. And notably, though IBM’s 4 Vs of big data (high-volume, high-velocity, high–variety and high-veracity) will all continue to grow, it’s forecast that data variety will be the biggest promoter of Big Data investment as businesses attempt to integrate many sources for enhanced analytics and progressive insights.
With many new branches fostered and supported by Big Data, 2017 will be a year of new roles, platforms, and possibilities for us all.
By Jennifer Klostermann
