Data has been created at an unprecedented speed, and properly collecting, analyzing and managing it can be overwhelming for businesses. While all information potentially has a value, finding the right and accurate data at the right time in an increasing volume of data can be quite a challenge.

Enabling enterprises to “find the signal in the noise” is how big data company Alation Inc. is growing its business. Today the company announced a new release of its flagship data intelligence platform. Alation 2020.3 further deepens machine learning and analytics to give companies confidence to make data-based decisions, according to said Satyen Sangani (pictured), co-founder and chief executive officer of Alation.

“The first thing that we’re releasing is a new experience around what we call the business user experience, which will bring in a whole new set of users into the catalog,” Sangani said. “The second … is basically around Alation analytics. And the third is around what we would describe as a cloud-native architecture. In total, it brings a fully transformative experience, basically lowering the total cost of getting to a data management experience.”

Sangani spoke with Jeff Frick, host of theCUBE, SiliconANGLE Media’s livestreaming studio, for a digital CUBE Conversation. They discussed how businesses struggle to get the best value out of data, how machine learning can help in this process, and the benefits reaped by companies that improve data access. (* Disclosure below.)

Creating a virtuous circle of data literacy and governance

To improve the use of data in businesses, it is necessary to allow people to search and obtain the information that is most relevant to them. To that end, Alation analyzes how data is being consumed within the organization.

“We determined that relevance based upon the other people in the enterprise that happen to be using that data,” Sangani explained. “And we know what other people are using in that company because we look at the logs to understand which data sources are used most often and which reports are used most often.”

Alation also adds context around the data to make it easier to identify. This context can come from a stewardship process implemented by a data governance framework or it can come from building better data literacy through having more analytics.

“But, however that context is built and revealed, there tends to be a virtuous cycle, which is you get more people searching for data. Then, once they’ve searched for the data, you know how to necessarily build up the right context, and that’s generally done through data governance and data stewardship,” Sangani stated. “And then once that happens, you’re building literacy in the organization so people then know what data to search for.”

Tools allow data culture assessment

One of the problems of companies that are building their data culture is that they have difficulty knowing what stage of the process they are in, Sangani pointed out.

Recent research has shown that there is a disconnect in how leaders view their business data culture and what the index score points to about their business. Most executives, 58%, overestimate the data culture of their companies, giving a higher score than that produced by the study.

Alation has an analytical tool to allow companies to better assess the level of their data culture, according to Sangani. It measures elements of how the organization is progressing in the use of information by teams, by data source and by use case, and then gives transparency to what is happening within the ecosystem.

“You can start to actually score yourself both internally, but also as we reveal in our customer success methodology against other customers, to understand what it is that you’re doing well and what it is that you’re doing badly,” Sangani explained. “And, so, you don’t need necessarily to have a ton of gut instinct anymore. You can look at the data … to figure out where you need to improve.”

When these data improvements start yielding results for companies, they often result in surprises, according to Sangani. Some business leaders realize, for example, that people are using data sets in a way that is not the most valuable or that the data is out of date.

There are also companies that realize they have wasteful data duplication. “In one case, we had a customer where they had the same data set procured five different times. They were spending $2 million overall on a data set where they could have been spending literally one-fifth of that amount,” Sangani concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage. (* Disclosure: This segment was sponsored by Alation Inc. Neither Alation nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE