The key to effectively dealing with data? Step one: Gather data. Step two: Analyze data. Step three: Leverage data insights for fun and profit.

Sounds simple, doesn’t it? But the amount of data out there is piling up, and the complexities of dealing with it are increasing.

The problem is that data alone doesn’t tell anyone anything. Nascent data assets must be prepared, shaped and formatted before operational reporting can occur. That’s even more critical when it comes to applying machine intelligence to coax valuable insights from the quagmire.

“When it comes to anything analytics, machine learning certainly, so much of what you have to do is actually prepare the data, shape the data, get the data to the right format, apply the model, fit the model, test the model, operationalize the model,” said Colin Mahony (pictured), senior vice president and general manager, Vertica Product Group, at Micro Focus International PLC. “Vertica’s a great platform to do that.”

Mahony spoke with Dave Vellante, host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the virtual Vertica Big Data Conference. They discussed the release of Vertica v10, machine learning, and how the company is uniquely positioned to provide data management across a multicloud environment.  (* Disclosure below.)

Busting boundaries between cloud and on-prem

Vertica started as an on-premises solution, a massively parallel SQL platform for enterprise analytics. In 2018, Eon Mode was announced, separating compute and storage and making Vertica the only company that could offer disaggregated compute both on-premises and in the cloud.

With Eon Mode, Vertica brought the advantages of cloud economics into the data center. It also allowed the isolation of workloads and set the stage for autonomous analysis.

“The database could actually start self-analyzing without impacting any operational workloads,” Mahony said.

Vertica v10, which launched this week, doubles down on the trend toward machine intelligence. “For all the hype that there is around it, this is real,” Mahony said. “People want to do a lot of unsupervised machine learning, whether it’s for healthcare, fraud detection, [or] financial services.”

Vertica v10 also introduces Vertica in Eon Mode for HDFS and Vertica in Eon Mode on Google Cloud, increasing the platform’s storage options. Google object store, Amazon S3 object store, HDFS, and Pure Storage FlashBlade are now all options, and Vertica is committed to remaining object store agnostic. This is a benefit to customers who don’t have to commit to one format or another.

“We don’t know what object storage platform is going to win, nor do we necessarily have to. We really embrace the different data formats,” said Mahony, explaining how customers with existing automated data pipelines don’t have to reload everything to take advantage of the Vertica analytics platform.

“We can go where the data is, connect into it, and we offer them a lot of different ways to take advantage of those analytics,” he added.

Born on-prem and proud of it

In a world where everything seems to be turning into software as a service, not being cloud native is an advantage, according to Mahony. Comparing Vertica’s service to cloud-born competitors, he said: “If you talk to a lot of our customers, they’re getting very good and very similar experiences with Vertica on the cloud. We stop short of saying we’re software as a service, because ultimately our customers have that control and flexibility. They’re putting Vertica on whichever cloud they want to run it on, they’re managing it.”

Being equally comfortable on-prem or in the cloud give Vertica’s platform flexibility across hybrid or multicloud environments. “We’re very good at operating in different environments with different formats, changing formats over time. And I don’t think a lot of the other companies out there are good at that,” said Mahony, who added that many SaaS companies even have trouble moving between the large cloud platforms such as Microsoft Azure and Amazon Web Services.

Efficiency is another area where Vertica beats the pure cloud competition. “It’s easy for cloud companies to play tricks and throw lots of servers at the environment when they start up,” Mahony said. “But for so many organizations, they’re dealing with on-prem and cloud. Frankly, looking at the bills they’re getting from these cloud workloads that are running, they really have to be cautious of that.”

Performance is yet another benefit, according to Mahony. “One of the things that we’re seeing against a lot of the other cloud databases is pound for pound, you know, you get on a tenth the hardware of Vertica running up there, you get over ten times the performance,” he said.

Despite listing the benefits of Vertica’s platform over its as-a-service competition, Mahony hints that a SaaS offering may be in the company’s future. It recently released the Vertica Advisor Tool, which has been a hit with customers, according to Mahony. The tool collects information from customer environments, both on-prem and in the cloud, and runs it through Vertica’s own machine-learning algorithms, analyzing the customers environment and automatically making recommendations.

“A lot of our customers have said to us, ‘We’ve tried managed service, tried SaaS often, and you guys blow them away in terms of your ability to help us automatically manage the Vertica environment and the system,’” he said. “Why don’t you guys just take this product and convert it into a SaaS offering?”

There’s “a lot of innovation and a lot of thoughts” going into how Vertica can do that, Mahony said.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the virtual Vertica Big Data Conference. (* Disclosure: TheCUBE is a paid media partner for the Vertica Big Data Conference. Neither Vertica, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE