New Text Analysis Definition: A Lesson from Sports

Text analysis definition and curiosities

Do you remember the movie Moneyball?

Moneyball tells the story of Oakland Athletics general manager Billy Bean and how he transformed the team in 2002 by focusing his methods of selecting new players on data rather than the traditional evaluation based on potential. Billy understood that they had all the data they needed—they just had to look at it in a different way.
Ironically, the story portrayed in Moneyball is similar to what is happening in the enterprise world. Organizations are faced with making decisions every day, and have a lot of data at their disposal for doing so. However, this data, often referred to as big data, comes from a wide variety of sources, is mostly unstructured (text such as emails, web pages, blog posts, social media content, etc.), and increases on a daily basis.

A new text analysis definition

Whether we’re talking about a 100-year-old baseball team or a successful business, making changes can be difficult.
When it comes to getting value out of combining structured data with unstructured data, the learning curve may be steep for organizations that hold tightly to their traditional business intelligence tools and are afraid to experiment with different approaches such as text analysis.

There is clear evidence that unstructured information cannot be easily and quickly managed with traditional approaches; however, businesses continue to put business intelligence at center of their strategy and limit text analysis practices by applying them keyword density or common pattern recognition where they are vastly under-utilized.

Data has not only become more available, it is more understandable

As with baseball before Bean, organizations have a lot of unstructured text that today can be analyzed in a different way. Text analysis has evolved, thanks to more intelligent solutions such as those that leverage cognitive computing to redefine strategic and business processes by combining computing power with human-like intelligence.

Intelligent text analysis is the “Peter Brand”(aka Paul DePodesta) that can change the rules of the game by enabling today’s organizations to understand big data, and thereby extract the maximum value from any amount of information.

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