Over the next few years, we are likely to see fewer articles about “big data” — not because data is going away but because the modifier “big” will seem inadequate to describe the tsunami of data washing over the business landscape. Nevertheless, for the next few years, big data will likely remain a term of choice. Bharadwaj “Brad” Chivukula, Senior Technical Manager at Nisum, predicts 2017 will be all about “putting big data to work.”[1] He adds, “Big data continues its march beyond the crater. [In 2017,] we can expect to see more mainstream companies adopting big data and [Internet of Things], with traditionally conservative and skeptic[al] organizations starting to take the plunge.” Chivukula is only one of the brave souls who has been willing to prognosticate about how big data will change the business landscape in the coming months and years. Below are predictions about big data from Chivukula and other subject matter experts.

The Amount of Data Generated will continue to Grow

“Whatever happens in the next few years,” writes Max Wegner (@appcessoriesuk), “there is one thing we can be absolutely sure about; big data will continue being big. Soon, we will start to talk about Zettabytes. This is a term referring to data equaling one trillion gigabytes. The main reason for this prolific growth with seemingly no end is the amount of devices we are coming up with. Several years ago, data mostly referred to structured data such as videos, images, music and documents. This type of data is still present today and is bigger than ever. But a new type has burst into the scene. To traditional data, now add data from your phone’s GPS, data from your smart home thermostat, data from increasingly smart vehicles and planes, data from millions of sensors embedded in almost everything and data from more places than you have ever thought of. We are buying more gadgets than ever before from wearables to smartphones to VR headsets. All these gadgets are constantly sending out data that needs to be processed and stored.”[2]

Big Data Growth will be Spawned by the Emergence of the Internet of Things (IoT)

The network of networks driving the exponential growth of big data is the Internet of Things. Chivukula observes, “Businesses are increasingly looking to derive value from all data; large industrial companies that make, move, sell and support physical things are plugging sensors attached to their ‘things’ into the Internet. Organizations will have to adapt technologies to map with IoT data.” Patrick Cole, Co-founder of Grecian-formula LLC, adds, “Businesses are increasingly looking to derive value from all data; large industrial companies that make, move, sell and support physical things are plugging sensors attached to their ‘things’ into the Internet. Organizations will have to adapt technologies to map with IoT data.”[3] Ann Bednarz (@annbednarz) predicts the demand for skilled IoT experts (i.e., software architects who can design both distributed and central analytics for IoT) will soar.[4]

Artificial Intelligence will Grow in Importance as Data Volume Increases

“By its very definition,” Wegner observes, “big data refers to incredibly large and complex data sets that cannot be processed or analyzed by traditional tools and methods. In looking for new ways to handle the ever increasing amounts of data, we have come upon artificial intelligence as the one of the best solutions.” He adds, “The analytical power of AI will prove invaluable to the analysis and use of big data. … In the next five years, AI and big data will continue to draw closer, becoming an inseparable pair and defining the future of big data analytics. Without AI, we might not have any other way to handle the boatloads of data coming our way.” Vishal Awasthi, Chief Technology Officer at Dolphin Enterprise Solutions Corporation, observes, “[Artificial Intelligence, Machine Learning, and Natural Language Processing] innovations have really exploded this past year but despite a lot of hype, most of the tangible applications are still based on specialized AI and not general AI. We will continue to see new use-cases of such specialized AI across verticals and key business processes. These use-cases would primarily be focused on the evolutionary process improvement side of the digital transformation.”[5]

Advanced Analytics will Turn Big Data into Smart Data

Data, no matter how large the database in which it is contained, is as useless as a seed lying fallow in a field if it is not analyzed. Laks Srinivasan (@LaksSrinivasan), Co-COO of Opera Solutions, writes, “Enterprises that apply Big Data analytics across their entire organizations, versus those that simply implement point solutions to solve one specific challenge, will benefit greatly by uncovering business or market anomalies or other risks that they never knew existed. … Discovering these unknown unknowns can enable organizations to make changes or fix issues before they become a problem, and empower them to make more strategic business decisions and retain competitive agility.”[6]

Real-time Streaming will become a Business Mainstay

Most experts agree the speed at which businesses operate today continues to accelerate. Business speed is another reason cognitive computing systems will be the foundation upon which digital enterprises are built. Cognitive systems can gather, integrate, and analyze data from both structured and unstructured sources and in many cases can do it real-time or near-real-time. Anand Venugopal, Head of Product (StreamAnalytix) at Impetus Technologies, predicts, “In 2017 (and 2018), streaming analytics will become a default enterprise capability, and we’re going to see widespread enterprise adoption and implementation of this technology as the next big step to help companies gain a competitive advantage from their data. … Streaming analytics will enable the real-time enterprise, serving as a transformational workload over their data platforms that will effectively move enterprises from analyzing data in batch-mode once or twice a day to the order of seconds to gain real-time insights and taking opportunistic actions.”[7] Eric Mizell (@EricMizell), Vice President for Global Solutions Engineering at Kinetica, adds, “The Cognitive Era of computing will make it possible to converge artificial intelligence, business intelligence, machine learning and real-time analytics in various ways that will make real-time intelligence a reality. Such ‘speed of thought’ analyses would not be possible were it not for the unprecedented performance afforded by hardware acceleration of in-memory data stores.”[8]

Big Data will be Democratized

Chuck Pieper, CEO of Cambridge Semantics, states, “I believe companies will begin to place different data storage systems into the hands of end users in a fast and efficient manner that has user self-direction and flexibility, democratizing data analysis.”[9] This democratization of analytics is primarily the result of analytics packages contained in AI solutions. According to Bednarz, demand for data scientists is softening because end users are now able to directly query smart machines using natural language. Wegner adds, “With a set of new tools and technology, everyone is turning into a data analyst.”

Summary

The devil is always in the details and the above predictions obviously just skim the surface of the topics they discuss. Many analysts predict that privacy issues will remain a hot topic of discussion as will standardization and cybersecurity. Chris Brandt concludes, “With the emergence of AI, cognitive computing will become a necessity. It will even become synonymous with analytics as businesses perceive the relationship and similarity between big data and analytics.”[10] Wegner adds, “We are at a point where so many new technologies are coming to a confluence and spawning entire new industries. Big data has numerous branches sticking out of it including AI, smart technology, wearables, robotics and many more. Together, these technologies will define the future. Big data has a big role to play in tomorrow’s world. As it gets better and smarter, expect huge impacts.”

Footnotes
[1] Bharadwaj “Brad” Chivukula, “The Top 5 Trends in Big Data for 2017,” Information Management, 7 October 2016.
[2] Max Wegner, “6 Predictions for The Future of Big Data,” Appcessories, 25 December 2016.
[3] Patrick Cole, “Big Data Trends For 2016,” DZone, 21 October 2016.
[4] Ann Bednarz, “8 big data predictions for 2017,” NetworkWorld, 12 December 2016.
[5] Daniel Gutierrez, “Big Data Industry Predictions for 2017,” Inside Big Data, 21 December 2016.
[6] Ibid.
[7] Ibid.
[8] Ibid.
[9] Ibid.
[10] Chris Brandt, “12 Big Data Predictions You Should Not Miss,” University Herald, 27 November 2016.