Brand-reputation management, market research, competitive intelligence, and customer-service needs have led to fast growth. Here what's driving interest.
Content analysis, the central text-analytics category, features software and services that decode text syntax and semantics and discern and extract information that may include entities (typically names of people, organizations, geographic areas, etc.); topics and themes; attitudes, opinions, and emotions, collectively under the sentiment-analysis heading; and events, facts, definitions, and relationships.
It's content analysis that automates sense making, for instance, extracting the good and the bad from forum comments such as "the room was incredibly clean... However, it became apparent there was no air conditioning and we would need to sleep with the window open... which led to a large amount of street noise." Content analysis capabilities are delivered by text-analytics tools and services, often domain-adapted and in some instances integrated with number-focused BI.
I expect the text-analytics market to sustain healthy annual growth, with rates in the 25%-40% range, in each of the coming years. We'll see a continued shift from on-premise software installation to Web services, with payment shifting to the subscription model. As-a-service text analytics provides for content annotation, classification, and enrichment, over the Web and within enterprise service-oriented architecture implementations.
Application programming interfaces (APIs) make it easy to plug new capabilities into line-of-business and analytical text applications. Further, the use of a third-party service, whether via an API or a dashboard or other user interface, lowers initial costs, eases start-up, and may afford access to a service provider's repository of social and online information, for instance, a cache of a couple of years worth of Twitter tweets or forum postings.
Independent of deployment mode, text analytics -- like BI dashboards, reporting, OLAP, and pivot tables -- is really just another business intelligence component, extending BI from data in structured databases to the world of text data sources. Leading vendors including IBM and SAP are now bundling text analytics within their BI suites, which will make the technology available to a significant number of BI users who are not currently working with text.
Given the importance of social and online text data sources, the variety of text analytics solutions and deployment options, and vendor commitment to bringing content analysis to the masses, I expect to report 2011 vendor text-analytics revenues that will easily clear the $1 billion mark.
InformationWeek contributing editor Seth Grimes is an analytics strategist with Washington DC consultancy Alta Plana Corporation. He chairs the Sentiment Analysis Symposium and the May 18-19 Text Analytics Summit.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
Join us for a roundup of the top stories on InformationWeek.com for the week of December 14, 2014. Be here for the show and for the incredible Friday Afternoon Conversation that runs beside the program.