Sailing the seas of enterprise data may get easier, with BigID’s latest release. The company hopes to make discovery simpler by letting individual users tune its automated discovery engine to their own needs.




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BigID is adding a feature that lets end users of its data intelligence platform manually adjust classification models, in an effort to make those more precise without the need for advanced coding knowledge.

The company announced today that the new feature, called classifier tuning, would allow users to adjust machine learning models in real time, leading to improved accuracy in the classification of machine-discovered data.

BigID said that the idea is to help businesses, which face increasingly complex data landscapes in their day-to-day operations, keep their information organized and protected. Across cloud, hybrid and local environments, and any number of different applications, organizations may have duplicated data sets in more places than they know, making close scrutiny important from both a privacy and an efficiency perspective.

A key part of that process is classifying that data — BigID’s existing products provide a machine-learning system that does this programmatically, but the company says that allowing end users to tinker with the process on their own is likely to improve its accuracy.

“Data owners can stop wasting time manually correcting inaccurate classification again and again from other systems,” said Maor Pichadze, senior product manager at BigID.

It’s an important capability, noted IDC research director Ryan O’Leary. The sheer number of different systems that might have access to particular sets of data, combined with the increased use to which enterprises are putting that data, means that accurate data discovery is a crucial consideration.

“Often enterprises get overwhelmed and have trouble classifying their sensitive data because of the volume,” he said. “In order to apply rules and policies to data it needs to be classified. Automating classification at scale helps solve a major problem for organizations and at scale.”

Integration with a wide range of different applications and systems, of course, is a key consideration for any data discovery tool looking to provide something close to a comprehensive overview, and O’Leary said that BigID appears to be aware of that, announcing a range of partnerships in 2022, including AWS, Splunk and HPE.

Classifier tuning is available now to all users of BigID’s discovery foundation products, according to a company spokesperson. It will not require any additional fees to use.

Jon Gold covers IoT and wireless networking for Network World.

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