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Text analytics derive value from unstructured data

Text analytics derive value from unstructured data 

This article is the second in a series about IBM’s white papers on how analytics can improve marketing efforts and managing a company’s finances. To download this whitepaper, please click here.

Authors Fern Halper, PhD, Marcia Kaufman and Daniel Kirsch note that text analytics can help firms gain insight from these vast amounts of unstructured data. They define text analytics as the process of analyzing unstructured text, extracting relevant information and transforming that into structured data that can be leveraged in many ways. Text analytics software use technology based on computational linguistics, statistics and other computer science disciplines to deliver ROI. Halper and her colleagues point out that the information derived from text analytics can be combined with structured data for analysis through a business intelligence lens. Iterative analysis could also be implemented to determine relationships and trends. The whitepaper’s authors suggest that companies might find text analytics software useful to enhance search in faceted navigation.

Analysts at Hurwitz & Associates see that more and more end users are implementing text analytics software. As a result of higher implementation rates, several trends are emerging in the text analytics software market. One of the trends is the adoption of social media analytics technology. Social media generates enormous amounts of unstructured data. Hurwitz & Associates has identified over social media analytics vendors. Text analytics are necessary to gain insight into the data embedded within social media channels. As a result of social media’s popularity, more analytics software vendors will include text analytics in their social media analytics solutions. 

Another trend is that it has become more popular to combine structured and unstructured data. Business analysts have discovered they can gain a far deeper understanding from the combination of structured and unstructured data than they would if they only analyzed structured data. The union of these two data types can improve predictive models, although the whitepaper’s authors point out that other forms of analysis can benefit from this mix. 

A third trend that the analysts identified is cloud-based text analytics solutions. The cloud continues to grow in popularity, and many vendors have chosen to leverage that fact. SaaS solutions appeal to businesses because they do not require an infrastructure investment or significant internal source of expertise to implement. The whitepaper authors claim that the cloud is one of the fastest growing delivery models for text analytics.  

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