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Data Analysis Using SQL and Excel
vBulletin Book Store > vBulletin books beginning with D
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Data Analysis Using SQL and Excel |
Author: Gordon S. Linoff
Published: 2007-10-01 |
List price: $45.00
Our price: $39.50
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Usually ships in 24 hours
As of: July 04th, 2008 01:23:59 PM
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Customer comments on this selection.
 Review from a non-statistician and business intelligence manager
"Data Analysis Using SQL and Excel" is an valuable resource for business intelligence and data mining practitioners in all industries. Having said that, I would like to offer some solid practical advice to potential readers that might not be fluent in statistics or data mining.
First, the reader should have a solid understanding of SQL. If the extent of your SQL interaction comes through a program on the level of Access, then you can still benefit from this book, but you will have to apply yourself more than others. Keep in mind, that proprietary releases of SQL might cause problems in directly translating the author's examples.
Second, if your statistics knowledge is a little rusty, have a secondary resource on-hand. Sometimes the definitions or explanations of the statistical concepts may not be as intuitive for some readers as they are for others.
With those caveats in mind, the reader need only to keep his or her patience and work through the concepts of the first 4-5 chapters. These chapters tend toward simple exposition of the concepts. For those with little patience, it may seem as if it is just a laundry list of concepts with little effort to tie those concepts into practical uses. Thinking like this is a great way to miss the enormous benefits of the book!
For me, the "Ah Ha!" moment came in Chapter 6 and 7. The concepts I had worked on in the previous chapters suddenly came together with customer tenure onward, when the techniques use will call to mind everything learned in the previous chapters.
In short, spend plenty of time in the first few chapters - the extra effort to master those concepts will only enhance the benefits of later chapters.
Lastly, there are a few odd differences between the text and the files downloadable from the web site. Whenever I hit a snag based on the text, opening the accompanying Excel files and seeing the formulas, queries or table/graph structures resolved all issues for me.
This is a text that will always have a place on my shelves.
A wonderful mix of theory and practice
If you work, like me, on data warehousing, data mining, analytical CRM or similar projects, this book will save you a lot of time, and provide you with a lot of inspiration.
Statistical concepts are clearly explained, and examples with very smart SQL queries and Excel sheets are shown.
For instance, no other book will explain you so clearly Survival Analysis, and how to practically implement it (I mean, with working code!).
As a previous reviewer wrote, why should you believe me? I'm one of the authors of another Wiley book, "MDX Solutions", and I earn my living by consulting with DaisyLabs, a Business Intelligence company.
Keep Gordon's book on SQL, and my book on MDX, on your desk, and no data analysis project will scare you anymore!
Nice Combination of Explanation, Business Examples and Execution
Wow - if you need a book that: 1. describes basic data analysis and statistical concepts in an easy to understand but thorough way. 2. uses real world business examples that you run into every day. 3. gives you the recipes of how to implement them in your business with real world computer tools like SQL and Excel. 4. and is written by a proven authority in the field (4 books and two decades of consulting). Then this is your book.
But why should you believe me? Just a little on my background. I wrote two books on databases and data analysis for McGraw-Hill: "Building Data Mining Applications for CRM" and "Data Warehousing, Data Mining and OLAP" and have led teams that have built data mining engines for super computers that later became Oracle's data mining engine, as well as implementing sophisticated data mining applictions (CART) in SQL and integrated between a relational and OALP database. Though I don't get to do a lot of 'data mining' in my current business I would definitely find this book very useful if I did.
Anyway, I thought this book was tremendously thorough in providing common sense explanations on everything from the Null Hypothesis to the Monty Hall Paradox (very cool). Buy this book if you want a single reference that will allow you to quickly solve real world business problems in a rational and doable way.
Invaluable Guide for Data Analysis
Utilizing data to drive results is critical to the success of any organization. Many know this to be true, but don't know how to go about it. "Data Analysis Using SQL and Excel" by Gordon Linoff successfully shows the way using a holistic approach of "data - analysis - presentation". Its success is based on a number attributes including....
1. Wide Audience: Different groups of people are addressed. Management and leadership will see what is possible with great examples (e.g. "Three Scenarios" on pg 333). "Doers" (e.g. analysts) get a clear view of the big picture along with the ever so important how-to aspects (which is often not included in other texts).
2. Popular Tools: As the title states, this book utilizes Microsoft Excel and SQL. Not only are these tools often readily available, but many people are familiar with at least one of these, if not both. This familiarity enables the reader to focus more on learning useful approaches than the tools themselves.
3. Methods: A host of useful methods are covered from Survival Analysis to the more traditional like RFM. All, especially those related to statistics, are explained well - simple but not so simple as to be inaccurate or incomplete.
In my opinion, "Data Analysis Using SQL and Excel" is invaluable to those who want to get the most out of their organization's data.
A "Must Have" Reference for Analysts in All Fields
Unlike textbooks related to stats and data analysis, this practical, "easy to read" book actually bridges the gap between theory and practice. The reader will understand both the "how" and "why" behind common approaches to data analysis. Best of all, the book targets a general audience and avoids intimidating language and notations. The author tackles the most common statistical concepts with colorful vinets. In fact, the explanations behind such ideas as "degrees of freedom" and "chi-square" are the clearest that I have ever seen in any reference or textbook.
Bototm line: whether you are a seasoned expert or novice, this is an invaluable, practical guide that will provide quick answers for anyone needing to analyze data using Excel.
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