If big data has reached a point where it has simply become essential to everything else, why are so many companies still struggling to put their data to good use?
Big data used to drive big page views and consulting fees, but now, argues Heudecker, “the various topics formerly encompassing big data evolved into other areas,” including the following:
If these sound like substitutes for the more malleable “big data,” in some ways they are. But I think Heudecker’s point goes broader.
Really, he’s arguing that big data isn’t something distinct that a company should, or can, do. Big data is not a strategy. It’s not a business objective.
Rather, big data is simply a way of describing data that is high volume or highly variable, or it moves at high velocity (or some combination of the three). Guess what? Most companies now have this, whether they’re a Google or a Kroger.
Such data, says Heudecker, is “no longer exotic,” but “common.”
As such, talking about big data as a meaningful category is far less interesting than talking about specific ways to put data to use within an organization. Those more interested in chasing buzzwords can turn their attention to the Internet of things, he mocks.
Whether because enterprises persist in misunderstanding big data or for other reasons, meaningful impact from big data initiatives remains elusive for most organizations.
This seems surprising, given rampant interest in data, as a Teradata-funded Forbes report shows.
big data importance
This is partly a matter of skills shortage. As Heudecker highlights, “Thru 2018, 70 percent of Hadoop deployments will not meet cost savings and revenue generation objectives due to skills and integration challenges.”
In other words, companies would do more with their data if they had the people requisite to manage the data infrastructure. The real problem goes deeper, though it is tied to the skills shortage.
The core issue is that it’s easier to say “big data” than it is to embrace big data. The former fits neatly into a PowerPoint presentation. The latter requires cultural change. As the Forbes report explains:
Part of the problem is that data-driven business models represent a break from the past that can call for a huge cultural upheaval. Almost overnight, employees must make data a priority, be willing to share data sets across departments and assume shared responsibility for data collection, quality and analysis.
A separate Booz Allen report uncovers the same reality: “The hard truth is that a key enabler to delivering on the biggest promise of data science is transforming organizational culture.”
“Hard.” “Huge.” “Dramatic.” These are the words used to describe the kind of change required to truly become data-driven. Most companies simply aren’t up to the task.
Have no fear, though: It’s the boss’s fault.
If you ask business leaders to name their strategic challenges, “making fact-based business decisions based on data” tops the list (48 percent of respondents to the Forbes survey). But when you ask them how willing they are to trust that data, a less rational picture emerges.
A Fortune survey of 720 senior business leaders that revealed that 62 percent tend to trust their gut rather than data, and 61 percent indicated real-world insight tops hard analytics when making decisions.
In other words, the problem with truly embracing big data starts at the top.
We have a long way to go, baby
This is why we’re seeing a boom in the adoption of such big data technologies as Hadoop, Spark, MongoDB, and Cassandra, even as returns on these investments sometimes stall. The problem isn’t the tools — it’s the culture. And that culture starts with the C-suite.
Big data is big business for vendors of data infrastructure. As Mark Torr details, the Hadoop vendors are on a tear. This same observation holds true across the big data landscape. So companies are clearly spending on the big data dream.
By: Matt Asay, VP of Mobile, Adobe
Originally published at www.infoworld.com
This excerpt is from InfoWorld. To view the whole article click here.