The 2016 Tech Trend That Wasn’t

Featured article by Bob DeSantis, Chief Operating Officer at Conga 

Heading into 2016, all anyone could talk about was big data. Industry executives and thought leaders predicted major advances in the space, and while 2016 did usher in some improvements to the technology, it failed to come close to the hype people built around it. While most organizations understood that they should be consistently mining and analyzing their data, they failed to understand the time and resources required to maintain the massive volume of data that was being generated. Despite the buildup and excitement around big data innovation, organizations were left confused, overwhelmed and ultimately disappointed when the tangible benefits of big data technology didn’t come to fruition. So will the big data hype finally live up to its name in the new year? Simply put, yes.

Looking back at the past year, the single biggest factor that caused big data’s 2016 letdown was the massively overwhelming volume of data that companies were trying to generate and manage. Organizations had so much data to handle that they simply couldn’t keep up. Not only did organizations lack the tools to manage this quantity of data, but they didn’t have the manpower necessary to utilize it. The talent shortage was top of mind for executives across industries. Another key indication of just how incapable organizations the impact felt by even a minor data center outage. A data center crash had the potential to leave IT departments scrambling for much more time than necessary, and the uncertainty that comes from this type of breakdown can cause long term damage.

As we head to 2017, the key differentiator between this year and last year’s success with big data will be organization’s willingness to take on the colossal challenge of integrating predictive analytics. Big data makes businesses faster and more efficient, and the past year has made it exceedingly obvious that it’s worth the time and investment. An increase in internal big data budgets will not only help increase productivity, but will also play a key role in keeping organizations relevant among competitors, which is always a top priority. All companies are data businesses now, so it’s time they start making decisions with that in mind.

Aside from an increase in organization readiness, another major factor to the impending rise of big data is the number of technologies being developed around it, specifically machine learning. There were some early-adopters that anticipated this relationship, but it’s clear that machine learning and predictive analytics go hand in hand. Big data gives the ability to not only analyze past information but to look to the future as well–and with how quickly data is generated, machine learning really lends itself to helping maximize these collections. Long term, it will be absolutely critical for almost any data-driven application to incorporate machine learning so that it can accurately digest the increasing amount of data our systems and processes produce.

Although we think we understand big data, we’ve just reached the tip of the iceberg. Big data is still in its infancy and there is a tremendous amount of innovation that we will see in the industry across all sectors in the year ahead. There are so many components that organizations have yet to take full advantage of, and we’re just now entering the technology revolution where predictive analytics is becoming table stakes. Once they’re fully incorporated, we’ll see organizations better able to remain competitive, leaving the door open to significant and rapid changes still to come.

About the Author

Bob DeSantis, Chief Operating Officer at Conga is responsible for the strategic direction and day-to-day operation of the company. He brings over 30 years of experience leading global sales, marketing, business development and operations teams. Prior to Conga, Bob was chief revenue officer at Blue Box Group where he launched and grew the company’s private cloud offering, which is now the core technology of IBM’s OpenStack cloud strategy. At Tier 3 he served as chief revenue officer and was instrumental in the sale of Tier 3 to CenturyLink. At DocuSign Bob held several leadership roles, including vice president of sales and managing director of DocuSign EMEA where he established their first international operation. Bob’s prior experience also includes sales, product management and product development roles with Procuri, FedEx, Dupont, Analog Devices and Kodak. Bob has a Bachelor of Science in Electrical Engineering degree from Boston University and an MBA from Temple University.