If you read the literature about new grads unable to find jobs except at McD's, one exception is a new category of job and profession called "Data Scientist" which started being used as late as 2009/2010. There now even is a CDSO--Chief Data Science Officer-- in some data intensive firms! IF your team doesn't yet have a CDSO, tell them to create the position and give it to you, especially if you're reading this review and considering purchasing this book. Entry data science: $90K range; Manager: $165K; CDSO: $220K including options, etc. (Source: DS assn.).
This little gem won't turn you into a data wonk overnight, but it IS a "condensed" Data/ MBA course (especially quantitative analysis in IT) showing the most current aspects of analysis from a big data vantage point. To be brutally honest, folks who got their MBAs even as recently as four years ago, and studied linear programming etc., are now having to once again reinvent themselves with the much more heavily statistical nature of mining, machine learning, Web X.o, etc.
My premise is: to be successful, we ALL need to be data scientists today, whether or not it fits our current job description! If you see any truth in that at all, this book is a must read. It avoids the deep math and algorithms behind the analysis, but gives very clear analogies, examples, and techniques in English to help with the most important steps: interpretation, relevance and use.
A recent trend in big data is "ala carte" dashboards, where users configure Sharepoint and other tools via Excel etc. LOCALLY. If you're not a quant, you ARE a quant CUSTOMER, and deserve to maximize the tools you have in front of you. Asking the right questions is 75% of getting that benefit. This book covers an excellent level of both overview and detail-- a nice and readable balance of why, when and how. It fits very sweetly in the vacant spot between Excel data manuals and 30,000 foot strategic tomes on the value of big data systems that frankly aren't really helpful unless you're a CTO.
3 bears again: the former can be TOO detailed, the latter not detailed enough, and this book just right-- Davenport figured out just the right missing balance between the power user, the user wannabe and us-- the practical users! Highly recommended. Oh, and if you DO want to get into this field, this text is a must have for a different reason--to see the balanced perspective of trenches users who need just the RELEVANT details in the midst of a very busy day.
Special tip: if you TEACH business or quant, you'd be doing your students a really big favor by incorporating many of this fine text's associations in your courses, as you'd be preparing them for many more of the real applications and issues they will see, with the practical knowledge of how they work and what they are and aren't suited for. Enough is covered to organize further reading and study for specialization and more depth in, say, the math, Excel, algorithms, systems, mining, software, etc.
Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.