To complete this Big Data tutorial, Affelt summarizes several examples of easy-to-use data visualization and predictive algorithm tools. The terms are reassembled into a “Big Data Glossary”—found within Chapter 2—which is a very helpful quick guide. Affelt does not assert that all LIPs need to know how to install and run IT infrastructure, but it is critical to have a working knowledge of the systems. In addition, common language will encourage opportunities to join Big Data teams. As technology advances, however, I question how fast the software and tools specifically described here will become obsolete, thus quickly making this extremely timely book …show more content…
A practicing LIP already has expertise in search and discovery, analyzing relevancy and assuring validity, as well as, delivering projects and communicating results. Affelt suggests ways to translate existing LIS job functions to work in data science. In Chapter 7, she takes the reference interview—a widely accepted LIS technique to ascertain a user’s information needs—and provides a step-by-step protocol to repurpose the method to assist in solving data challenges. Walking the reader through real world scenarios very much illustrates the process. Another compelling section of the book details the value of a law LIP’s knowledge over pre-programmed software which can be summarized as, Big Data plus a LIP equals better data. The book’s emphasis on human factors in data science is strong and it also presents Big Data projects that failed as a way to stress the problems of false interpretation in analysis as