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7 Reviews
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4 of 4 people found the following review helpful
5.0 out of 5 stars cool author, and written with humour. Unfortunately this does not make it any easier, 4 Oct. 2014
By 
J. Norman (london) - See all my reviews
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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.
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2 of 2 people found the following review helpful
5.0 out of 5 stars Makes relatively complex concepts very simple, 28 May 2014
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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...
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2 of 2 people found the following review helpful
5.0 out of 5 stars This is a good data science book even for people with experience on the subject, 17 May 2014
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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!
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1 of 1 people found the following review helpful
4.0 out of 5 stars A brilliant foundation with actionable explanations, 4 Dec. 2014
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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.
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1 of 1 people found the following review helpful
5.0 out of 5 stars So far, excellent, 4 Aug. 2014
I've only been through the first 4 chapters so far and it's fun.
So far, I've learnt techniques for segmentation, how to analyze text data and an optimization scenario. I'm looking forward to applying these to work.
The Excel primer in the first chapter should be printed and distributed to the whole company - it's perfect, contains all I taught to my team.
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1 of 1 people found the following review helpful
5.0 out of 5 stars What a brilliant book! I teach Advanced Excel to qualified accountants, 20 Dec. 2014
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What a brilliant book! I teach Advanced Excel to qualified accountants, and this book is a real boon.
This book will help those transitioning from being good at Excel, to having the basic knowledge concerning data science. Excellent.
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5.0 out of 5 stars A truly amazing book, everything I've ever needed for my job, 19 Feb. 2015
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A truly amazing book, everything I've ever needed for my job.
Sometimes I wonder why there are 4 year degrees out there when we could rather just purchase a book like THIS!
Thanks John
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