The Data Catalog looks not at the metadata but at the data itself and uses machine learning to gain visibility into the data and provide insights. Fourteen machine-learning algorithms are used to find implied relationships, she said.Further, Sokolovsky explained, the solution can also see how data flows through an enterprise and provide a view into data redundancies.Among the drivers for this technology are what Sokolovsky called “the rise of intelligent technology,” expanding data sources, the monetization of data assets, and increasing costs to the enterprise in managing and leveraging data. “We had been aiming at IT, but now we’re addressing business users,” she said.”It’s a move toward business analytics.” Io-Tahoe today announced the general availability of its smart data discovery solution, with the addition of a new machine-learning Data Catalog feature that enables the creation of business rules and policy definition.The announcement reflects the growing need for data to drive business decisions, and for BI tools that the business side can use to generate their own reports. But with data stored in disparate silos, it has been difficult for organizations to govern their data and glean important insights from that data.Io-Tahoe’s solution not only discovers data, but it also can uncover undocumented relationships. The solution works across silos of relational databases and data lakes to discover data and populate it into a repository, then “can generate a map of data relationships that has usually only been understood by data scientists,” Io-Tahoe CEO Oksana Sokolovsky told SD Times.