Data Smart: Using Data Science to Transform Information into Insight Paperback – 25 Oct. 2013

This book is an excellent practical application of commonly used advanced analytical techniques for data analysis in Excel. I was skeptical that this was possible before purchasing the book and partly bought out of curiosity of to what extent it could be pulled off, but I was pleasantly surprised.Those with a strong background in statistics and SAS/SPSS/R will find it interesting and find it useful for the purposes of helping other understand what they are doing (i.e. it isn't magic) - but the target audience would be for those trying to gain business insight (probably in SME's) who are technically able, but who only know and / or have access to one tool for solving the problem - i.e. Excel. There are a lot of people in this situation, and this book could dramatically widen their horizons when considering issues such as optimisation or customer insight.Ultimately the author himself ends the book by stating that Excel isn't really the right tool for the job, and introduces R as an open source alternative. The demographic at which this book is aimed would most likely would not have considered this a possible path before they picked up this book, but I believe by the end of it most will give it proper consideration as a means to best apply the methods detailed within the book.As an aside, the author has a quirky and amusing style, which went down well at least with me, such that I read the first 4 chapters in one sitting...

As a software developer I wanted to dip my toe into Data Science as it is clearly a key trend for tech and for wider society. This book promised to be an accessible introduction. If Excel is its tool of choice it couldn't be too advanced! However, while the author's writing style is wonderfully unpretentious and entertaining, and he makes the content as easy as I can imagine it being made, these are not toy techniques. This is proper data science that has genuine applicability in the real world. If you can get your head around the contents of this book you'll be well-placed to add real value in any organisation.This is a very valuable book that is well worth the effort.

I took delivery of this book 4 days ago. Since then I was posed a question by a client who wanted to look at 3 year forecast of marketing potential. I am comfortable with this however the data they had was not brilliant and there were a lot of unknowns and statistical anomalies which made this extremely difficult. This book really enabled me to get to grips with how best to tackle these sorts of questions in a clear and concise way and ensure you are keeping an eye out for outliers and noise. It has since spurred me on to order another couple of more in-depth books on statistics and this has since proved to be an excellent foundation book on which to build expert knowledge.

I almost gave this a lower rating because it is a challenging read - I thought a couple of times of packing it in halfway through which never makes you feel good about a book.Thankfully I didn't, because it is a difficult subject matter, but there aren't any problems with the writing or content.I have had to over it quite a few times to "get it" and there are still things I don't fully understand, but at least I can replicate to get results. Some readers might be able to grasp it first time, but I think many won't unless they already know about things such as Clustering and Exponential Smoothing.If you are looking for a basic intro to Data Analysis you should avoid this, but if you are looking to really get stuck in, then buy it. Be warned what you are letting yourself in for: just browsing it or reading once and putting on the bookshelf will be of no use whatsoever. I've spent at least 30 hours on it so far.Overall the content and the ideas are brilliant, and the guy is really really funny - still doesn't make it any easier.

It helps you develop strong intuition for algorithms you might already have used. The author is so knowledgeable that can explain "cosine similarity" without any mathematics and you still get the full feeling of it (try Wikipedia instead). After a while you get into the mentality of "how would I explain this with Excel" - which is a good habit to have. Before you apply to Tb of data, showcasing with a spreadsheet what you are trying to do and verifying that the outputs give meaningful results could save tons of money and time on data science projects. Great book - great idea - very well written. It also reads way faster than a typical 350 page book because of the graphs/Excel screenshots etc. (this is good). Well done - we want more like this!

What a book! challenging but incredibly useful. If you are looking for proper learning on clustering and advance analytics this is a great book for the purpose. If you are looking for something quick read and move to the next book...don't buy it.The author has a great sense of humour. Also, he is a top class on what he does...otherwise he wouldn't lead the analytics team at mailchimp.

I'm relatively new to data science and the calculation complexities - the concepts are presented very well in the book, but I struggled with putting them into practice. Appreciate technical people trying to dumb this type of stuff down for decision makers, but once I again I feel this book hasn't managed that.

Good book; but aimed more at the beginner of data analytics (excel heavy and some R)