Expert Predictions: The Future of Big Data and Business 20 Years From Now

01/08/2017 06:09 pm ET | Updated Jan 09, 2017

Big data is everywhere these days. From fashion to transportation, enterprise to small business, big data is a topic that every entrepreneur, executive, and investor is paying attention to.

Big data is formally defined as follows: extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

This broad definition has left many holes to fill and while everyone agrees big data is a big deal, what the future will look like is still heavily debated.

At Future of Everything, we cover what the future will look like for different industries and for today’s article we reached out to 10 big data experts with one question:

What will be the impact of Big Data on business 20 years from now?

“Big data, like most technology, is a tool and a means to an end, but it cannot substitute human judgment, innovation and management skills. That said, I believe there are two major applications of big data that will significantly impact the future of business. The first is making deductions based on large data sets, such as determining who that market for golf balls based on collective past purchases of things like golf clubs. These models help people find the things they need, reducing search costs, and work well with anonymized data, allotting consumers the benefit of being in large ‘group discounts’. The second model is inductive reasoning, which makes it possible for businesses to target consumers based on their other behaviors. For example, it looks at an article about a cat that you clicked on and offers you cat food. By design, this involves personal data and can have positive and negative effects. It can also isolate people into smaller and smaller circles, where the articles you see and the ads you get are only seen by you. The technical viewpoint is that firms achieve ‘perfect discrimination’ and maximize the producer surplus.”

Javid Muhammedali, VP of Product Development at Monster

“20 Years is a long ways out to predict, but first of all, the technology behind big data will become entirely invisible. It will be seamlessly woven into the fabric of both your daily and business-focused life. Think about your phone – when you speak into it, when you text somebody, you’re not thinking about the mechanics behind the signal. You’re not thinking about the combustion engine powering your car, you’re just hitting the gas pedal and driving. That is how big data and the technology of the future will come to be perceived. Over time, information collection mechanisms, and usages, will be folded into the basic decision-making at every level of society, without visibility into the amazing complexity going on underneath the surface.”

Elliott Yama, Chief Data Analyst, Apttus

“You only have to look through the headlines of late to see that the rise of robotics and automation is provoking mainstream debate. Implemented strategically automation has no need to steal our jobs or spell the end of manual labor as we know it.

In fact, when set in place correctly it will be barely visible and can deliver significant business value, reduce security and compliance risks and free up staff time to focus on more valuable tasks and new ways of working..

Automation tools will help manage big data effectively, extracting value from it that will truly enable companies to leverage existing enterprise skills, best practices and processes to manage this new digital environment. Therefore, robotics and automation need not to be seen as a threat but rather as an opportunity for businesses, one that should be championed louder in this Fourth Industrial Revolution.”

Paul Appleby, EVP BMC Software

“If companies are able to unlock the power of large-scale data, they will make 100 major decisions a year instead of 2-3. They will be able to predict the outcomes (and respective probabilities) of these decisions with much greater accuracy, and be able to take external and internal input in real-time. They will be able to optimally leverage each employee in terms of both output and satisfaction. They will be able to create and design products in a much more systematic and scientific manner, rather than the black box of "innovation" today. But I don't think it will take 20 years!”

Krishna K. Gupta, Founder, Romulus Capital

“Under the accelerating pace of technology advancement, 20 years hence is no longer a "knowable" future in the sense of making tangible predictions that follow a traceable path forward.

So if we can't predict that pagers will become mobile phones or that bulletin boards will become the internet, what can we say about how Big Data will impact business? One way is to consider that reality is the biggest data of them all. In other words, any and all forms of big data will capture more detail about what's happening in real life.

But to what end? The answer is replay and simulation. Imagine your business is facing a tough decision about a key customer. Your systems will replay past interactions, injecting thousands of variables but ultimately converging on a likely prediction. Or suppose you are training an employee and want to accelerate her learning curve. Put her in virtual reality and let her learn. This is how environments like the NFL already operate. The technology is getting better, at lower cost.

We can't know the future, but we can know about the future. We already know that details matter, and that those details are somewhere in Big Data.”

Mike Finley, Co-founder, AnswerRocket

Lotame Photo credit: A.E. Fletcher Photography

“In the next 20 years, the ways that business access and source data will advance greatly. This will level the playing field and provide a much more expansive view of ‘big data’ as a whole and particularly in the martech landscape. 

The core differentiation from today will be the types of artificial intelligence used by companies. Consumer data will be lighter, easier to use and more normalized - similar to what we’ve seen with credit reports and financial information over the past 20 years. Consumers will accept the personalization, targeting, product recommendations and other benefits of their data being used. ”

Andy Monfried, CEO and Founder, Lotame

“In 20 years, Big Data analytics will likely be so pervasive throughout business that it will no longer be the domain of specialists. Every manager, and many non-managerial employees, will be assumed to be competent in working with Big Data, just as most knowledge workers today are assumed to know spreadsheets and PowerPoint. Analysis of large data sets will be a prerequisite to almost every business decision, much as a simple cost/benefit analysis is today.

This doesn’t mean, however, that everyone will have to become a data scientist. Self-service tools will make Big Data analysis broadly accessible. Managers will use simplified, spreadsheet-like interfaces to tap into the computing power of the cloud and run advanced analytics from any device.

What future workers will need, instead, is an intuitive understanding of the possibilities, limitations, and ethical implications of Big Data, as they combine human and algorithmic judgment on a day-to-day basis. That’s why DeVry University’s Business Intelligence and Analytics Management concentration is geared toward applying the results of analytics throughout an organization. It’s also why we are infusing technology, including analytics, into all our programs, to help prepare our graduates for careers that increasingly demand literacy in Big Data.”

Russ Walker, PhD, Senior Professor, College of Business & Management at DeVry University

“Deep learning relies on big data analytics and digs through vast volumes of information from enterprise databases, files and emails as well as social media and consumer purchases, to recognize small and larger hidden trends, giving your business the power to exploit opportunities and create a competitive advantage.

Deep learning requires a high-performance IT infrastructure that is purpose-built to analyze, and - crucially - learn from, large data sets in real-time. In turn, the underlying storage for deep learning must have the agility to accommodate and process a variety of data types at speed. This is one of the reasons why software defined storage, thanks to the high degree of flexibility it offers, has jumped to the top of the wish list for most enterprises.

Deep learning algorithms are exploding in the industry as organizations are under competitive pressure to support the increasing sophistication of data modelling and simulation to develop data as a basis for managerial or technical decision making. In the future, larger organizations are likely to succeed only if they have exploited the opportunities that deep learning can unlock in order to adapt their business models and practices to the ever-evolving market dynamics.”

Jerome Lecat, CEO, Scality

“Big Data is going to reshape business over the next 20 years to the degree that the Internet reshaped business over the last 20 years. In 1996, Google didn’t exist. Nor did Facebook, Twitter, SnapChat or any other social media platform—actually, barely 35 million people used email.  Amazon and the digital store front was still in diapers. Twenty years later and digital transformation has reshaped how the modern enterprise operates. Big Data is going to have the same level of impact. Machine Learning and Artificial Intelligence (AI) is still in its infancy, yet organizations are already delivering immense business value with automated machine learning platforms. New human-computer interfaces coupled with machine learning will upend how businesses interact with customers, much like the Internet-Smartphone duo sparked the social media revolution. Machine learning-centric IT systems will be at the core of business operations and communications, much like the Internet is at the center of today’s business. Big Data and machine learning will also drive a major rethink of the supply chain as efficiencies can be gleaned from more complex, hyper-local distribution and supply networks. All of this will be driven by highly automated, real-time data and machine learning platforms such as SAP Business Objects Predictive Analytics and SAP HANA.”

David Jonker, Senior Director of Predictive Analytics at SAP

“Today, companies focus on automating their business processes. However important, these investments provide a relatively modest return, measured in eliminating errors and repetitive work. The promise of Big Data is far more exciting. Every process and device leaves a trail of data describing what it did. This data is immensely useful for effective decision making. In the future, Big Data will inform, predict and model the best potential outcome for every decision humans will be faced with. No more guesswork.

Think of it this way. Today, people make decisions based on their individual experience or their capacity or willingness to research. With Big Data, every individual will have access to the experience of every related precedent action, process, and result that have been statistically evaluated and modeled, so that the next choice we make is better and more appropriate for the situation we face, personally and professionally.”

John Schwarz, CEO and co-founder of Visier

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