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TDWI Checklist Report | Eight Steps for Using Analytics to Gain Value from Text and Unstructured Content

April 28, 2014

Organizations that aspire to be data driven cannot afford to limit users’ data analysis to structured data: that is, the alphanumeric data types that have been carefully defined, modeled, and stored in standard spreadsheets, relational databases, and data warehouses. In the course of business processes, operations, and customer interactions, enterprises generate far more than just structured data—in particular, most are swimming in massive amounts of text.

Drawn from both internal and external sources, text files form a potential gold mine of insights that could help organizations reduce costs, improve customer relationships, speed response to events, and innovate with products and services. Business intelligence (BI) and data warehousing (DW) systems are adept at delivering the numbers, but if users do not have access to unstructured and semi-structured text such as customer comments, field personnel notes, and social media, they will be blind to contextual information that could help answer questions about the numbers. Exploratory analysis of text could reveal emerging trends that do not show up in BI reports.

Text analytics covers a range of technologies and practices for analyzing text, extracting relevant information, and transforming sources by applying structure so that analysis can be repeated and adjusted over time. Software solutions combine techniques from natural language processing, statistics, and machine learning. One of the goals of text analytics is to accurately extract entities, facts, concepts, themes, and sentiment. With the popularity of social media, many enterprises are interested in performing sentiment analysis. However, interest is expanding across industries to other uses, such as in healthcare, where text analytics helps doctors understand the full context of patient symptoms and engage in evidence-based medicine.

Making use of modern data visualization, text analytics solutions enable users to explore text on desktops and mobile devices. Business users, not just specialized text analysts, can use the solutions to derive value—for example, by aggregating findings from text with their analysis of structured data. Following TDWI’s previous Checklist Report on this topic, How to Gain Insight from Text, this Checklist discusses the relevance of text analytics for improving user experiences with the semi-structured and unstructured textual big data now at their disposal.

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