In 2007, Hurwitz & Associates fielded one of the first market studies on text analytics. At that time, text analytics was considered to be more of a natural extension to a business intelligence system than a content management system. However, in that study, we asked respondents who were planning to use the software, whether they were planning to deploy it in conjunction with their content management systems. It turns out that a majority of respondents (62%) intended to use text analytics software in this manner. Text analytics, of course, is the natural extension to content management and we have seen the market evolve to the point where several vendors have included text analytics as part of the their offerings to enrich content management solutions.
Over the next few months, I am going to do a deeper dive into solutions that are at the intersection of text analytics and content management; three from content management vendors EMC, IBM, and OpenText as well as solutions from text analytics vendor TEMIS and analytics vendor SAS. Each of these vendors is actively offering solutions that provide insight into content stored in enterprise content management systems. Many of the solutions described below also go beyond providing insight for content stored in enterprise content management systems to include insight over other content both internal and external to an organization. A number of solutions also integrate structured data with unstructured information.
• EMC: EMC refers to its content analytics capability as Content Intelligence Services (CIS). CIS supports entity extraction as well as categorization. It enables advanced search and discovery over a range of platforms including ECM systems such as EMC’s Documentum, Microsoft SharePoint, and others.
• IBM: IBM offers a number of products with text analytics capabilities. Its goal is to provide rapid and deep insight into unstructured data. The IBM Content Analytics solution provides integration into IBM ECM (FileNet) solutions such as IBM Case Manager, its big data solutions (Netezza) and integration technologies (DataStage). It also integrates securely with other ECM solutions such as SharePoint, Livelink, Documentum and others.
• OpenText: OpenText acquired text analytics vendor Nstein in 2010 in order to invest in semantic technology and expand its semantic coverage. Nstein semantic services are now integrated with OpenText’s ECM suite. This includes automated content categorization and classification as well as enhanced search and navigation. The company will soon be releasing additional analytics capabilities to support content discovery. Content Analytics services can also be integrated into other ECM systems.
• SAS: SAS Institute provides a number of products for unstructured information access and discovery as part of its vision for the semantically integrated enterprise. These include SAS Enterprise Content Categorization, SAS Ontology Management (both for improving document relevance) and SAS Sentiment Analysis and SAS Text Miner for knowledge discovery. The products integrate with structured information; with Microsoft SharePoint, FAST ESP, Endeca, EMC Documentum; as well as with both Teradata and Greenplum.
• TEMIS: TEMIS recently released its Networked Content Manifesto, which describes its vision of a network of semantic links connecting documents to enable new forms of navigation and retrieval from a collection of documents. It uses text analytics techniques to extract semantic metadata from documents that can then link documents together. Content Management systems form one part of this linked ecosystem. TEMIS integrates into ECM systems including EMC Documentum and Centerstage, Microsoft SharePoint 2010 and MarkLogic.
Filed under: advanced analytics, Big Data, Business Analytics, Content Management, Text Analytics, text mining Tagged: | content analytics, content insight, EMC, Enterprise Content Management, IBM, OpenText, SAS, TEMIS