Without utilizing the power of data, most businesses trying to survive the modern world will fall behind other organizations as information becomes a new currency.

With data, businesses can track consumer metrics, employee data, track what’s trending in their industries and much more. Data products, such as those offered by Select Star Inc., streamline the data collecting, analyzing and management experience using a variety of technologies, such as artificial intelligence to bring the best data experience to its users, according to Shinji Kim (pictured), founder and chief executive officer at Select Star.

“We should treat data as a product; hence, we should have a way to manage data better. We should catalog them, and we should put contracts in place,” Kim said. “Whenever there is a request for data, these are the processes that they should go through.”

Kim spoke with theCUBE industry analyst Rob Strechay, during a CUBE Conversation from SiliconANGLE Media’s livestreaming studio in Boston. They discussed data products, AI documentation and other upcoming features coming to the service.

Data: The lifeblood of modern companies

There is an important distinction between a data product and a product set. While a data set collects data, a data product creates value with the data in some way, enabling businesses to make decisions and carry out processes easier than without the product, according to Kim.

“Most of the time, data products are things like your recommendation model, fraud detection model, or it could be personalization model designed for a specific purpose,” she said. “Because it is like a product, it can be used for different features and purposes, can be augmented, can be iterated, and applied in different places. That’s my definition.”

Select Star is taking advantage of the data and technology boom that’s occurred since the pandemic took hold of the world. As AI takes the digital world by storm, Select Star sees potential in the technology, announcing AI documentation, a service that generates documents from scratch with very little context provided in the prompt.

“Our original automated documentation was about filling in all the descriptions of columns and tables whenever we see either duplicated tables or whenever we recognize any data that’s been transferred as is, because that’s one of the details that our column-level lineage will track,” Kim said. “It was cool to see how close we can get even when there is no prior documentation whatsoever, and now we can help our customers to really kickstart their data documentation and data dictionary.”

The other big feature Select Star released this year is Snowflake Cost Analysis, now allowing businesses the option to scale their cloud utilization and data, effectively giving them more control of their costs. For companies looking to better manage and optimize their cloud data warehouse cost, the first step is slicing and dicing the data to allow for segmentation by user, team and warehouse for dashboard, table, or query analysis, according to Kim.

“When you start doing that, you can start seeing the topmost queries that are driving most of the costs. What time of the day or day of the week is causing this, or which warehouse,” she said.

Here’s the complete video interview, one of many CUBE Conversations from SiliconANGLE and theCUBE:

Photo: SiliconANGLE