It’s no secret that the information age has transformed business in radical ways. But somewhere between the constant need to upgrade IT systems and provision new and different resources, there’s the sobering reality that data volumes are increasing at a furious rate—and the need to interpret data and put it to maximum use is fundamentally rewiring and revamping businesses. Today, IT systems and business processes spin a tight orbit around data, which has emerged as the fuel for the digital age.
Big data is at the center of this universe. As organizations look to gain new insights into an increasingly complex and chaotic world, it is redefining everything from retail and entertainment to healthcare and financial services. In fact, almost no industry or government institution remains untouched by big data. For channel pros, this brave new world represents both opportunities and risks. Resellers, solution providers, and MSPs that help customers put big data to work are positioned for greater performance and profits. “Big data represents a sizable opportunity,” says Anurag Agrawal, CEO of market analysis firm Techaisle LLC.
How can channel pros navigate this emerging space? How can big data help SMBs grow their businesses more effectively? And what are some of the issues and barriers that prevent channel pros from offering attractive big data solutions and putting them to work? While there’s no single approach for steering through the emerging world of big data, it’s clear that it is a concept that channel pros cannot ignore. “The promise of superior, data-driven decision making is motivating SMBs to either invest in or investigate big data technology,” Agrawal explains.
Moving Beyond the Data Basics
Although big data has elicited plenty of hype and media buzz during the last few years, this doesn’t diminish the validity of the concept. Techaisle predicts that SMBs worldwide will spend an estimated $3.6 billion on big data solutions by 2016. That’s up from $867 million in 2012.
Indeed, businesses are using big data and analytics to solve an array of business challenges, ranging from understanding customer behavior and delivering more relevant promotions to solving complex science, engineering, and mathematical problems. Big data is all about becoming more agile and flexible so that an enterprise can adapt to fast-changing conditions and operate on a real-time basis.
JT Lee, founder and data scientist at HCONN Inc., a Merriam, Kan., systems integration firm that specializes in business analytics solutions, says that the reach of business intelligence, analytics, and predictive analytics is revolutionizing business. “It isn’t only for big companies, it’s for everyone,” Lee says.
For example, retailers are using big data to arrange shelves and displays that better match consumer behavior. Hotels are turning to it to understand loads and pricing patterns. Charities are using big data to make decisions about everything from marketing techniques to solicitation approaches. And police are adopting predictive analytics to assign officers to locations that are likely to encounter problems. “Big data is able to unlock a remarkable number of insights by finding hidden patterns and trends,” Lee says.
In many cases, big data not only incorporates existing data tucked away in databases and other repositories, it plugs in unstructured data from emails, text messages, online chats, social media sites, and more. In fact, social listening systems can now identify emerging trends and changing tastes for products and services. They can also analyze online conversations to generate leads and marketing strategies—or help healthcare providers, the travel industry, and retailers better understand consumer preferences. Not surprisingly, these insights can increase sales, improve the efficiency of operations, and boost customer service.
But these opportunities are also accompanied by a number of challenges. “Big data is not a clean-cut technology or space. The term doesn’t help businesses build a strategy or assemble the right collection of tools, technologies, and assets required to drive business performance,” explains Josh Greenbaum, principal at Berkeley, Calif.-based Enterprise Applications Consulting and author of IEEE’s Computing Now blog. He points out that success in the big data arena doesn’t occur as a direct result of specific vendor tools and solutions. An organization must identify a collection of processes, workflows, and methodologies that can deliver improved results.
Agrawal agrees that big data isn’t a plug-and-play solution. “It requires a certain level of IT sophistication and a history in linear investments in information technology to be successful,” he says. Ideally, resellers, solution providers, and MSPs guide clients through the space and help them build both a strategic and technical foundation. “Channel pros must help their clients unlock business value,” adds Vijitha Kaduwela, founder and CEO of Kavi Associates, a Barrington, Ill., consulting firm that specializes in big data and analytics solutions.
Channel pros who position themselves on the front side of the big data curve could reap benefits for years to come, Kaduwela says. He sees big data as a lucrative niche, aided by the emerging industrial Internet. These devices and sensors will stream an enormous wave of data into the enterprise. Yet, gaining the necessary expertise and experience to provide strategic consulting and integration services requires far more than attending a conference, reading a book, or sitting in on a series of training sessions. “It requires both broad and deep knowledge of how to tap into the power of data and put it to work. There’s a need to understand how to connect technology infrastructure, integrate different technology solutions, and use data to create business value,” he explains.
Vincent Dell’Anno, leader at Accenture’s big data practice, says that big data takes a giant step beyond the reach of business intelligence, data warehousing, and other data-focused tools of the present and past. Rather than moving data through an organization in a serial way, big data initiatives create a point-to-point model that is based on agility and flexibility. Mobility, cloud computing, and other digital tools magnify and amplify the effect. Within this context, he says, “It is critical to identify choke points and understand the way today’s technologies fundamentally change how an organization taps data and puts it to use.”