At its core, big data consists of large sets of information culled from various sources and then analyzed to derive statistical value. These metrics become particularly useful for measuring industries, humanistic tendencies, behavior and interactions. IBM’s Watson supercomputer, for example, is a cultivator of big data, as are the back-end analytics engines companies like Facebook and Google have access to.

Previously, such data collection was a mundane and particularly tedious task. In the late 1980s, a data analyst had an especially boring job. Archaic green-screen machines spit out seemingly endless spreadsheets that were riddled with errors — and required human oversight at all times.

These days, things are innately different. Big data has been made especially useful thanks to the cloud, the Internet of Things (IoT), social media, and other data gathering methods (think Google Maps, Apple Pay, Apple Watch, Fitbit and others). Large companies routinely sell or furnish this data to analyzing firms and think tanks, which then use it to determine and predict tendencies. Most commonly, big data is used by marketing firms to derive analytical patterns to create trendsetters in the digital hemisphere.

Of the most shocking big data statistics, this one takes the cake: According to Cloud Tweaks, "2.5 quintillion bytes of data is produced every day." A quintillion bytes would have 18 zeros following it; just to give you an idea of its monstrous size. The publication further helps us understand that big data really consists of all kinds of stored and shared data — ranging from photos hosted on social media sites to images beamed down to Earth from orbiting satellites in space.

The truth is that without big data, cloud computing wouldn’t be as powerful as it has become; and without cloud computing, there wouldn’t be such a thing as big data. As Qubole explains, “The rise of cloud computing and cloud data stores has been a precursor and facilitator to the emergence of big data.”

In fact, Amazon Web Services, Google Cloud Platform, Microsoft Azure, Rackspace, and others are big data servers as well as cloud hosters. In essence, they work hand in hand, harmoniously procuring data, hosting it and serving it to the masses while feeding statistics back to the think tanks and companies that provide the hosts.

Big data and the cloud are forever intertwined to help one another, and neither exists without its cohort. This leads to questions: Does big data matter to growing businesses? And if so, what place do small to mid-market businesses have in today’s analytics-driven world?

Leveraging big data to inform business strategy

Small to mid-market businesses (SMBs) across various industries are using big data insights to drive multiple top and bottom-line gains. Financial and retail companies, for example, are combining the data from their ecommerce, call center and catalog channels to drive a deeper understanding of their customers’ evolving needs and the products that best satisfy them.

Also, healthcare is saving millions of dollars with proactive population care, real-time analytics, recommendation engines, workforce optimization and billing intelligence. In addition, small to mid-market manufacturing businesses are deriving repeated 1% improvements from optimization algorithms, prescriptive maintenance, quality metrics and time-to-failure analyses.

Big data experience begins with employees and company culture

While the benefits of big data are apparent, knowing how and when to apply it (and how to do so quickly and efficiently) takes time, which is a major barrier for small to mid-market businesses. Small to mid-market businesses need to foster company cultures that prioritize big data throughout their organizations in order to gain the necessary analytics experience. At the top, for example, executives should recognize the potential of the cloud and big data and be willing to sponsor new projects, while enabling managers to spearhead projects, keeping them laser-focused on business needs and goals. On the ground, the associate must identify opportunities for growth or savings and feel empowered to deliver that message back at the top.

[What are some of the benefits that analytics offer to companies of all sizes, according to McKinsey?]

For those trying to initiate and cultivate big data culture, small to mid-market businesses should start small and partner with a company that has a proven track record of successful projects. As success breeds success, a few quick wins will pave the way to larger, more impactful changes. As those changes percolate through the business, the employees and the culture will follow.

Keeping big data in mind when hiring

When scaling up, small to mid-market businesses should hire employees who can grow into one of three positions: business, data, or analytics. Think of a savvy manager, a data-smart engineer or a skilled data scientist. However, one employee should not be expected to perform all three roles, as specialization and velocity would be compromised, diminishing visibility and stalling a business’s analytics growth. Instead, a team should be formed around each function. If a small to mid-market business can’t afford that level of initial investment, it should start with a few strategic hires and supplement as needed with an outside partner.

The availability of inexpensive cloud big data platforms has given small to mid-market businesses access to more data from more sources than ever before. Those businesses are combining data from multiple in-house operational systems, folding in public data, and deriving insights that would have been impossible just a few years ago. From understanding customer habits to measuring spend, big data allows small to mid-market businesses to unlock more ways to grow and prosper as successful businesses. 

Curt Cornum, Vice President-Chief Solution Architect at Insight Enterprises.