Beyond the Three V's of Big Data

VALUE IS PARAMOUNT

While veracity can’t be overlooked, experts are in agreement on which V is most crucial when it comes to Big Data and the bottom line. “From a business point of view, I think that value is probably the most important thing,” Goodarzi says. “The first three V’s are really talking about architecture, infrastructure, representation of data—things that are important to IT organizations and, by far, less interesting to the business guys. The business guys really don’t care about the first three, they only care about the value they can extract from the data.” He adds that executives often expect the analytical teams at their organizations to “hide the first three V’s [volume, velocity, and variety] and only generate the last V—the value that is fundamental to the success of the business.”

According to Duncan, the concept of value is essential for organizations to succeed in monetizing their data assets. Duncan defines value as a “property that helps identify the purpose, scenario, or business outcomes that analytic solutions seek to address” and adds that it “helps confirm what questions are to be answered and what actions will be taken as a result, and defines what benefits are anticipated from collecting and analyzing the data.” He also asserts that value is a motivating force when it comes to developing new and innovative ideas that can be tested by exploring data in different ways.

York agrees: “The ability to pull valuable information from Big Data and use that information to build a holistic view of the customer is absolutely critical. It’s no longer just an option to develop one-to-one relationships with customers; it’s a requirement. And to build that relationship, companies have to leverage all the customer information they can to personalize every interaction with them.” She adds that by using such information to lead customers on a personal journey, companies can help ensure that customers will stay with them long term, and even become brand advocates. Value is derived from making the data actionable, she concludes. “We can have all the information about a customer, but it’s what we can do with it that drives value for the business.”

The Three V’s model of volume, velocity, and variety is useful for organizations that are just beginning to take control of their data, and certainly should not be forgotten by enterprises that have advanced further in their management of customer information. According to York, the first three V’s are equally important—in the digital age, companies have accumulated more data than ever before, are pulling data from a variety of sources, and are increasing the rate at which that data flows, and that a combination of these three factors can help businesses create relevant, personal, and one-on-one customer interactions.

Nevertheless, deriving value is the ultimate business goal for any enterprise. According to Duncan, the standard Three V’s model does not satisfactorily identify any data properties from a business usage perspective—as he puts it, the model does not articulate a “So what?” factor. Noels agrees: “Even though Big Data—and data in general—provides [businesses] with a lot of capabilities, the challenge for businesses is to make sure that they adapt how they think about the processes of their marketing campaigns, and also how they report on those and how they define [key performance indicators].”

“You’re trying to get to the value; that is the name of the game—everything else is ancillary to that,” Goodarzi says. For his part, Renner says that despite his career working with data, “data for the sake of data is really not even interesting. The question is, how do you turn that data into value. It’s figuring out how to use that data to optimize the monetization side [that is important].” In the end, the Three V’s model for Big Data is a useful jumping-off point; but then it becomes about the ultimate goal, one businesses must not lose sight of: driving value.

Assistant Editor Sam Del Rowe can be reached at sdelrowe@infotoday.com.

Related Articles

IBM Storage Solutions Team Up with Hortonworks Data Platform

The collaboration aims to enable IBM clients to use existing and future investments in IBM storage to deploy Hadoop-based Big Data applications.

Information Builders Releases WebFOCUS Business User Edition

At its annual user conference, the business intelligence vendor introduces self-service tools to help non-technical users "harmonize, visualize, operationalize, and monetize" their data.