Enterprise Search, 2nd Edition

Chapter 18. Text and Content Analytics

The reason for including this chapter on text analytics is because there is a high degree of commonality in the underlying technologies of search and text analytics, and as a result, any enterprise search strategy should take into account the current and potential adoption by the organization of text analytics solutions.

Over the last few years, there has been a substantial amount of hype around Big Data, with most of the major players in the IT industry promoting the view that a significant investment in Big Data is all that an organization needs to make in order to achieve its business objectives. There is no doubt that managing Big Data can make a substantial contribution, but gradually it seems that a balance is emerging around the extent to which Big Data applications need to be complemented by search and text analytics technologies.

The core reason for this is that organizations have a mix of both structured and unstructured information. A survey undertaken by Unisphere Research in 2014 with sponsorship from IBM shows that 25% of respondents indicated that structured data represented no more than 50% of the data under management. Even where the majority of the data under management is structured data, as may be the case in financial services, retail services, and telecommunication services, the unstructured data may provide very important information that enables the data to be placed in a business context. As a result, the value might ...