Text analytics changes business processes
Text analytics is an emerging field, but it has already delivered significant promise to companies. According to a recent MicroScope report by industry insider Ankush Korla, the field of business intelligence was once constrained to information that could be encapsulated in numerical values. Text analytics and natural language processing represent a new type of analysis that can expose the latent value of new reserves of data.
Korla stated that new text tools can describe the "relevance" of text rather than simply finding it. For years, efficient search engines have been able to create lists of documents matching a certain phrase. Text analytics and machine learning, however, have led to algorithms that can determine sources' importance and meaning in context.
Korla also mentioned that the potential of text analytics goes well beyond a company's own data and and can incorporate the larger internet. Social media contains a wealth of freely offered sentiment data from the public. The information can be unlocked with advanced tools.
Shifts are required in business thinking now that text analytics is on the rise. Data warehousing expert Bill Inmon reported for BeyeNETWORK that text does not fit correctly in traditional relational databases. He emphasized that while some may not want to change data storage strategy, those able to will find ways to transcend old limitations.