Anomalo, the company reinventing enterprise data quality, is adding a major innovation, Workflows, to its second product Unstructured Data Monitoring, introducing a hub for managing and monitoring unstructured data.
Unstructured Data Monitoring lets enterprises extract insights and identify issues from the vast volumes of unstructured data stored in their data warehouses, data lake, and cloud storage locations.
Anomalo’s Unstructured Data Monitoring with Workflows furthers the company’s mission to provide data trust across all data types and all data use cases, according to the company.
“Everyone’s talking about unstructured data for GenAI but the real breakthrough is solving for both quality and insights within this type of data. You can think of our Unstructured Monitoring product and Anomalo Workflows as building blocks that can be assembled in thousands of configurations to achieve pretty much any customer use case for unstructured data quality or insights. Take one of our large retail customers who is trying to mine support tickets and call logs to understand why customers are unhappy. That kind of analysis wasn’t easily possible before Anomalo. Just as we redefined data quality for structured data, we’re now helping enterprises trust and extract value from unstructured data at a scale no other tool can match,” said Elliot Shmukler, co-founder and CEO of Anomalo.
Anomalo’s first product uses AI to automatically detect issues in structured data, letting teams resolve any hiccups with their data before making decisions, running operations, or powering AI and machine learning workflows.
With Anomalo’s Unstructured Data Monitoring product, enterprises can curate unstructured text documents and evaluate them for data quality around various document and document collection characteristics, including document length, duplicates, topics, tone, language, abusive language, PII, and sentiment.
Customers can quickly assess the quality and fitness of a document collection and identify issues in individual documents, dramatically reducing the time needed to curate, profile, and leverage high-value unstructured text data.
In addition to Anomalo’s 15 out-of-the-box issues, customers can create their own custom issues to look for and designate what classifies as high or low quality for their documents with custom severity scores.
Customers can tailor the platform to their specific use case and get results fast, the company said.
For more information about this news, visit www.anomalo.com.