Big Data Management

Micro Focus IDOL Named a Leader Among Document Focused Text Analytics Platforms

Micro Focus | July 20, 2022 | Read time : 03:00 min

Micro Focus
Micro Focus today announced that it has been recognized as a Leader in The Forrester Wave™: Document-Oriented Text Analytics Platforms, Q2 2022 report for its unified AI-based data analytics platform, IDOL. For Micro Focus, the 2022 recognition demonstrates the success of IDOL's ongoing strategy in addressing diverse use cases for extracting maximum data value and delivering holistic insights to accelerate better business decisions.

In its evaluation, Forrester reviewed a dozen document-oriented text analytics platforms and assessed the strengths and weaknesses of each offering based on a comprehensive set of evaluation criteria grouped into three categories: current offering, strategy and market presence.

The report states, "IDOL's strengths include document capture, including one of the most comprehensive document-focused data integration and document-workflow orchestration capabilities (partially based on Apache NiFi), native image analytics, comprehensive NLU (over 1,000 entities), a multitude of OOTB ontologies for data enrichment, document level text analytics, and secure handling of sensitive data (including PII redaction in audio, images, and video)."

"Micro Focus IDOL's ability to comprehensively address all unstructured data analytics needs is unmatched. "We believe IDOL's proven performance has earned it recognition as a Leader from Forrester."

Rick Carlson, VP of Product Management, Information Management & Governance, Micro Focus

Today's organizations are faced with fragmented and siloed information that is driving the need to easily connect to data across disparate content repositories, and even cloud-based platforms. IDOL helps organizations to meet this challenge by unlocking hidden insights by revealing trends, patterns and relationships and is just one of the ways Micro Focus helps customers bridge existing and emerging technologies in the race to digital transformation.

Micro Focus IDOL provides AI and machine learning unstructured data analytics of all text and rich media with support for more than 1,300 data formats. It enables out-of-the-box access to more than 150 data repositories behind and beyond firewalls, (for example, Documentum, Dropbox, and such) that allows data to be indexed wherever it resides without disruption.

In addition to being a Leader in the Forrester Wave: Document-Oriented Text Analytics Platforms Report, IDOL has also been recognized as a Strong Performer in The Forrester Wave™: People-Oriented Text Analytics Platforms, Q2 2022 report.

About Micro Focus
Micro Focus is one of the world's largest enterprise software providers, focused on solving the IT dilemma—how to balance today's needs with tomorrow's opportunities. We deliver mission-critical technology that helps tens of thousands of customers worldwide manage core IT elements of their business. Strengthened by our strategic services and support organizations, and an extensive partner network, our broad set of technologies for security, IT operations, application delivery, governance, modernization, and analytics provides the innovative solutions organizations need to run and transform— at the same time.


User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.


User Entity and Behavior Analytics (UEBA) is a cybersecurity technology and approach that focuses on analyzing the behavior of users and entities (such as devices, applications, and systems) within an organization's IT environment. By using advanced data analytics, machine learning algorithms, and artificial intelligence, UEBA aims to detect and prevent cyber threats by identifying anomalies, deviations, or patterns in user and entity activities that might indicate potential security risks.

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