The true value of data analytics is not measured by the market caps of the top vendors or average industry revenue growth, but by what users can accomplish leveraging the technology, the possibilities for which extend far beyond merely boosting the bottom line.  That was the underlying theme at the recently concluded HP Vertica Big Data Conference in Boston, when SiliconANGLE founder John Furrier broke down how the database fits into the new paradigm of decision-making with Wikibon’s Dave Vellante and Jeff Kelly over two action-packed days of hard-hitting discussions.

“We’re seeing the revenue related to Big Data products and services growing faster than we thought, but the value that practitioners are creating from Big Data technologies is increasing at least as fast if not faster than what we’re seeing on the vendor side,” Kelly highlighted on theCUBE’s opening segment for the event. That premise was demonstrated clearly in the large number  customer case studies showcased at the conference, which were as diverse as the users themselves.

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Usurping the traditional warehouse

The exhibitors ranged from bleeding-edge tech startups such as Etsy Inc. and Cardlytics Inc. to well-established names like the United States Postal Service. That mirrors the divide in the analytics landscape, which Kelly sees as split into two distinct camps: the digital native companies leading the way on adoption and the slow-moving enterprises scrambling to catch up. The latter group has been uncharastically quick to do so, according to a recent Wikibon study that found over 90 percent of  organizations have either already began migrating or are planning to move workloads from their data warehouses into Hadoop by the end of the year.

That shift is taking a heavy toll on traditional platforms from the likes of Teradata Corp., but less so on Vertica, according to Kelly. The database owes that resiliency to combination of factors, he detailed, including optimization for specific web workloads, efficient resource utilization and a scale-out architecture that takes advantage of commodity hardware.  In that regard, Vertica is quite similar to Hadoop, an advantage HP is exploiting to push ahead of the competition.

“What Vertica is positioning themselves as is yet another SQL-on-Hadoop option.” Kelly said. “What Vertica has going for it is that it’s a much more mature database than some of the other SQL-on-Hadoop options.”  The platform attempts to bring the hard-learned lessons from the old world of data management to the new world of analytics, an approach that has earned it a unique position in the marketplace.

“Everybody is coming to the recognition that the traditional data warehouse is just not getting it done, and the economics of modern platforms such as Hadoop are just so attractive. Vertica sits in the middle and is an arbiter of those two worlds,” Vellante remarked in the next roundtable session on theCUBE at the end of the first day of the conference.

Showing promise for practitioners

In addition to far superior economies of scale compared to traditional data warehousing systems, Hadoop also offers the freedom to combine different types of information from multiple sources. Yet Kelly said that the biggest advantage of the platform and modern analytics in general is not so much in the flexibility of the technology but the new use cases that it enables.

“The enterprise data warehouse is about looking in the rearview mirror. Big Data analytics is about looking forward, making predictions understanding customers better and being proactive,” he said. “That’s the big shift we’re seeing among practitioners.”

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It’s those practitioners who are applying analytics to address business objectives and identify new growth opportunities, but so far, HP has not been particularly effective in engaging that audience, and not for a lack of determination. The company is actively trying to draw developers to Vertica, but its efforts have been hampered by what Furrier sees as an inherent marketing disadvantage against newer players.

“HP is not getting it done with developers. They’re early and they’re attracting a different audience,” he observed. “They’re not winning the hackers yet, that’s not a very short-term objective. I don’t think that a developer will look at HP and say ‘wow, I really want to work with HP!’ just like they don’t look to IBM.”

Despite not having too much traction in developer community yet, Vertica is nonetheless a major force in the database market. With Hadoop taking hold as the standard for large-scale batch processing, HP’s platform  is taking on a complementary role in the analytics jigsaw, providing a stable environment for  workloads that the open-source framework was not built to handle.

“Vertica is not your one-size-fits-all data lake. It’s for loading data fast, MPP, doing things that are conducive to that type of architecture,” Vellante told Furrier and Jeff in the opening segment for the second day of the summit (video above). “You can’t do that with a traditional enterprise data warehouse and you won’t necessarily be able to do that with Hadoop, but at the same time, it’s probably not gonna be as cost-effective as the data lake.”

But as advantageous as it can be to have a centralized repository where access to information is not limited by silos,  implementing the data lake model remains a distant goal for the vast majority of organizations. Like the abundance of use cases for the platform, that too was reflected at the conference.

“Either I’m missing something or the crowd is missing something,” Vellante concluded at the end of theCUBE’s coverage of the event. “I didn’t sense that there was a sense of urgency to move to this new paradigm, except for the guys who already there – the Big Data practitioners leading the data-driven charge – who are going to gain market share, gonna grow faster the competition and disrupt existing businesses.” He expects that group of early adopters will push the slower-moving “fat middle” of the market to follow suit in embracing analytics, a trend that HP fully intends to be a part of with Vertica.

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