Beyond the Three V's of Big Data

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When Blizzard Entertainment introduced its massively multiplayer online role-playing game World of Warcraft in 2004, the video game developer and publisher didn’t have data in mind. But with the game reaching more than 12 million subscribers during its peak in 2010, the company realized that it could improve the gameplay experience by collecting and analyzing the massive amounts of data it could glean from its players. While Blizzard utilized data and analytics to improve gameplay in World of Warcraft after the fact, its latest game, Overwatch, is being developed entirely with data in mind—according to Jon Gleicher, manager of business and gameplay insights, “almost no decisions are made without understanding the data first.”

Big Data is everywhere. But to harness its potential, businesses must understand the challenges that come with collecting and analyzing Big Data. One frequently proposed model focuses on the “Three V’s of Big Data”—namely, volume, velocity, and variety. These three factors serve as guidance for Big Data management, highlighting what businesses should look for in solutions. But even as businesses have started to get a handle on the three V’s, two other V’s—veracity and value—should prove just as consequential, if not more so.

According to Alan Duncan, research director of data and analytics at Gartner, volume is the ability to ingest, process, and store very large data sets. Duncan notes that the definition of “very large” can vary by business and is dependent upon the particular circumstances of the business problem, as well as the preceding volumes used by that business. Afshin Goodarzi, chief analyst at 1010data, offers a more specific definition: Volume is “the number of rows, or the number of events that are happening in the real world that are getting captured in some way, a row at a time.” Accordingly, “the more rows that you have, the bigger the data set is going to be.”


In today’s digital age, having huge volumes of data is hardly rare. The proliferation of mobile devices ensures that companies can gather more data on consumers than ever before, and the rise of the Internet of Things will only increase this plethora of data. Moreover, businesses will have even more information on customers as they begin to use one-on-one messaging channels to interact directly with them.

“The sheer volume of data available to us is greater than ever before. In fact, in many ways, nearly every human action can be quantified and logged in a bank of data that’s growing at an incredibly fast rate,” writes Meghann York, director of product marketing at Salesforce Marketing Cloud, in an email. “All of this data can be turned into actionable insights that drive business decisions and can help transform every customer interaction, create operational efficiencies, and more.”

According to Goodarzi, this increase in data volume is paired with a simultaneous increase in speed—a process that he illustrates using the example of the New York Stock Exchange: “More and more trades are taking place on the New York Stock Exchange as a function of time,” he says. “If you look at 10 years ago or 15 years ago, what the volume was versus the volume today, you will see that the speed with which that volume is increasing, as well as the volume itself, are both picking up.” These twin increases, Goodarzi says, have forced IT staff to spend more time trying to figure out how to process and analyze that data.

Steven Noels, chief technology officer at NGDATA, believes that velocity is the key V of the three V’s. According to Noels, a seismic transition is occurring as campaign-based marketing morphs into personalized, one-on-one interactions with customers, and marketing is becoming simply a convenient term to describe the overall process of customer experience improvement. Often, he says, a customer will visit a company’s site or use its mobile application but only for a short amount of time—marketers may have just seconds to gather customer information and deliver a relevant response based on that information, usually just one message or offer. Noels says that this quick turnaround time “requires you to process all of that real-time behavioral data as fast as possible. If you only understand that your customer was on your Web site the day after, you’re not able to contact them anymore.” York shares a similar take: “One aspect of a successful customer journey is being able to send the right message at the right time to the right customer. Timeliness and relevancy are the foundation of delivering personalized customer experiences in real time.”

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