New Book Review: "Enterprise Analytics"
New book review for Enterprise Analytics: Optimize Performance, Process, and Decisions through Big Data, edited by Thomas H. Davenport, FT Press, 2012, reposted here:
This book is a collection of eighteen essays on enterprise analytics by fourteen different authors, ten written or co-written by the editor, who also wrote "Competing on Analytics: The New Science of Winning" with Jeanne G. Harris, and "Analytics at Work: Smarter Decisions, Better Results" with Robert Morison and the aforementioned author (see my reviews), both of whom contributed to this book as well. The topics in this text are a bit more varied than in the earlier efforts of the editor. Rather than focusing on how analytics can be utilized to compete in the marketplace, as was the case in the first book, this latest entry moves in the direction of the second book, which is how to practice analytics. Not in the sense of in-the-trenches toolsets or statistical methods, but at a level more akin to enterprise architecture.
After providing an overview of analytics, the authors direct the reader to topics such as applications and technologies of analytics (approximately 50% of the content), analysts and governance, and case studies. While over a dozen authors contributed to the material, in my opinion it was edited well so that the writing style does not vary to the point of distraction, and the editor reasonably constrained the scope. Chapter 1 ("What Do We Talk About When We Talk About Analytics?") and Chapter 2 ("The Return on Investments in Analytics") were especially well done.
It is about time that someone defined the analytics space, and the table that Davenport provides to break down the three types of "business analytics" (as opposed to other types of analytics, such as "web analytics"), along with the accompanying discussion, is well recommended reading so that everyone can finally get on the same page in this area. There exists some overlap with the table that was provided in Chapter 1 of the second book mentioned above ("What It Means to Put Analytics to Work"), but it is clear that more thought has been put into this subject in the ensuing years. Although the questions that are addressed by analytics have stayed virtually the same, they are more specific in some cases, and the new breakdown into three types of analytics (descriptive, predictive, and prescriptive) from the original two types of analytics (information and insight) in my opinion is much more intuitive.
Along these same lines, I also especially appreciated the definitions and material focused on "engagement" in Chapter 5 ("The Analytics of Online Engagement"), and how one firm measures online engagement with a generalized model it devised. The discussion provided in Chapter 9 ("Analytical Technology and the Business User") on how the multipurpose BI environment of the past, which did not serve business users well, is evolving into environments that are either single-purpose for business users and professional analysts, or multipurpose without the assumption that simplification is needed for business users, was also well done.
The last two words in the subtitle of this book, "Optimize Performance, Process, and Decisions Through Big Data" might be the catalyst for some to pick up a copy of this book, but this is not a book specifically about Big Data. As is noted in the introduction to this text, "This book is based primarily on small-data analytics, but occasionally it refers to Big Data, data scientists, and other issues related to the topic. Certainly many of the ideas from traditional analytics are highly relevant to Big Data analytics as well." My recommendation to readers specifically interested in the Big Data space is to check out the O'Reilly Strata series on Big Data (see my reviews).