The Accidental Analyst: Show Your Data Who's Boss Paperback – 8 May 2012

I really was looking forward to getting this book, as it promises a great deal and has a catchy title (if you find yourself to be one!) Alas no! Starting with the production quality, the book is a softback - but not like most softbacks - it is one of those limited print runs that are done in small batches to keep costs down where the covers are equivalent to 110g paper and the pages are like 60g i.e. really thin and nasty! There is no colour in the book (except for a splash on the cover), just grayscale, which again keeps costs down and would be acceptable if it didn't look so rubbish. Worst of all is the content - I could forgive all the above if the content was insightful, thoughtful or even original. It isn't. The only thing to recommend this book is the fact it isn't "Dream On" by John Richardson (which is the worst book I've ever had the misfortune to purchase/read/touch!) I could have written this book (in about half the amount of pages) and kept it as a downloadable .pdf (which would actually be a higher production quality standard than it currently is). Don't waste your money - even for free I'd think twice!!

The Accidental Analysis is a great book for anyone who has a block of data and needs to make conclusions from it. The focus of the book is on Visual Analysis which is the act of building visuals from data to solve problems and identifying actions. The example in the book focuses on business intelligence and sales in particular, but the framework they lay out can be used by anyone doing any type of analysis with numbers.The book is an excellent resource for anyone who finds themselves doing analysis without any formal training or experience in analytic or statistics. I was a humanities major in college, now working in the business world, and found the book to be very easy to understand. The focus is on practical applications and real world situations. You don't need to know anything about statistics or data management to use the book, though if you do, I think you'd still likely get a lot out of the book.Instead of talking about equations, they lay out a basic 7 step framework that is very easy to understand. The first part of the book walks you through forming questions to guide your analysis, and the practical aspects of collecting data, correcting problems in the data, and joining multiple data sources together. The second part of the book focuses on the analysis of the data. Particularly how to chart the data, analyze what's going on, and communicate the results. If you are a fan of Stephen Few or Edward Tufte's work you will appreciate the advice given in the second part of the book. Additionally the book is filled with lots of tips, tricks, and best practices.The book is laid out very well and you always know where in the process you are through the tabs printed on every page. As they teach the steps they walk through a hypothetical situation from start to finish using a Pet Store's sales data that builds throughout the book. This allows you to see the steps in practice. They use Tableau to build the visuals in the book so this makes it a great resource if you're wanting to go beyond the authors' other book Rapid Graphs with Tableau, which focuses on learning the software. But the book is written in such a way as it stands alone from any particular BI software and could easily be used with Excel, Access, Business Objects, Cognos, JMP, Micorstratgy, QlikView, R, SAS, SPSS, or Tibco Spotfire.

I have really enjoyed this book and found it grew on me as I read it. I think it is an excellent way to think about and even rethink analytics in the real-world. What's most interesting is that some of it is obvious after a year or two of analysis but much of it is not, until you have read it and then you think, of course we should show ROI or percentiles or year over year growth on the same graph!This book is loosely structured around the scientific method but reshaped for addressing business analytics with a decidedly visual bent. They have converted the scientific method to the 7 C's of analysis and have great examples throughout the process. The 7 C's are: Choose questions, Collect data, Check data, Clean data, Chart the data, Customize the analyses and Collaborate the results. I found their tabs on every page (a pictogram of where you are in the 7 C’s) of the book a great way to quickly orient yourself as to which C you are in and what stage of the analytic process you are working in.This book is black and white, which I enjoyed more than I expected since the examples are beautifully illustrated, even without color. In fact, the examples have me rethinking my tendency toward excessive color, which I see may impede my point. Finally, there is great advice for those of us who would rather stay at our desk and program- get out there and ask more questions of the business “owners”, making certain these conversations shape your approach to the analysis and especially how you present your results. I have found this advice quite useful in my work already!

Good introduction of concepts but not enough depth if you have any experience in the field. Stephen Few's books provide more depth and are accessible for beginners.

I highly recommend this book to anyone who is not trained in analytics and business insights. I come from a Sales background and currently have a postion in sales operations. I wanted to learn if there is a "process" to analytics like we commonly have in sales. This book will provide you the basic framework for working on a project including the right questions to ask and to confirm with your associates what they are looking for. I also liked that it follows a "case study" through the book so you can see how different graphical tools can be used to answer questions. I also purchased Tableau 8 to use which is a great Business analytics tool. The author also has a book on creating graphs with the software. I am very pleased with this book and both authors did a GREAT job.

MS. MCDaniel does a good job explaining how to perform data analysis when you've never performed it before. She outlines the three steps for sound data analysis: (1) collecting the "raw" data; (2) summarizing the raw data by using counts (aggregate) and percentages; and (3) presenting the data in charts and tables.I would recommend this book for beginners to immediate data analysis enthusiasts. Those with advaced data analytical skills might be disappointed with the lack of any new revalations. You would be better off reading Steven Few's superb book "Show Me The Numbers." That's the de facto data analysis bible.