Replies to This Discussion

Permalink Reply by Vincent Granville on October 17, 2011 at 4:57pm

Also, I believe that

• This is the first book about data science
• This is the first analytic book with content mostly coming from a social network
• This is the first free e-book generating revenue via sponsors (vendor contributions) and where marketing is both internal and via contributors offering the book for download on their website

Indeed, we believe that this is the new way to sell and market a book. In many ways, it is the exact opposite of what traditional publishers still do as of today: selling the book for a fee, not having sponsors, and having very expensive marketing strategies. Eliminate all of this by proceeding as follows:

This new book publishing model has two components:

1. Identify your own best posts on your network - and publish it in PDF format with tons of clickable links to your your web site. 
2. Have a Resources from vendors (AKA sponsors) section - these are the guys who will pay you money, but you should also offer free contributions (from "affiliates") in exchange for having your book available for download on affiliate web sites. 

Make the book available for free, use your network to market it.

This creates an exploding mix where you generate traffic very fast, at no cost, and generate revenue directly from the book (via the sponsors), and indirectly to your network (web site) due to increased traffic and thus increased ad revenue.

(Note: we think that one day, we'll make a paper copy of our e-book - but the original version will be digital) 

 

Permalink Reply by Theodore Omtzigt on October 19, 2011 at 4:15pm

I read the ABbook5.pdf with the expectation to see a data mining version of "Numerical Recipes". I am a big fan of the "Numerical Recipes" books as they provide accessible introductions to very complex and rich topics.

However, the description you offer here indicates that this is a different type of book: a new kind coming from a social network. So having properly reset my expectations, here is my feedback:

- as different problems have different scope, the recipes also widely differ in scope and applicability. As a service to the reader, if there can be some editorial control applied to the descriptions to add/unify that scope and applicability, the recipes will become much much better. Some supporting links like Wikipedia would help as well.

- the three parts are as different as they come, so I would suggest that you truly separate the parts into their own three distinct books. I do not see a reason to combine them in the same book, nor would I use the book in that way. By separating them you gain clarity and agility, and I would say from an operational/advertising/sponsor point of view, you gain more revenue and opportunity.

 

- love the idea to create a new publishing format, although it doesn't seem to go as far as Wikipedia, or platforms like the StackExchange or Quora (Q&A driven sites), or a marketplace like Spiceworks. I am excited to see if you can make this eBook work as it sits between Wikipedia and StackExchange.

 

- Take a look at Spiceworks as a model: right now I don't believe that the world of analytics is big enough to support something like Spiceworks for Analytics, but as big data and self-service BI are becoming essential elements in the arsenal of modern business the class of knowledge workers that deal with analytics will steadily grow. IMHO, fundamentally, Spiceworks works because IT professionals have a big say in the budgets they need to operate. Analytics professionals have a much smaller impact on budgets in the traditional enterprise, although they do sit at the strategy table in the analytics startups that we all love. If that trend continues, the Spiceworks model could work.

Permalink Reply by Vincent Granville on October 28, 2011 at 6:16pm

I have uploaded a new version (56 pages, 22 contributions, updated bio). If you can not download it, refresh your browser, then try again. The URL is the same. Many new articles will be added in the next 2 weeks.

Permalink Reply by Avijit Paul on February 13, 2012 at 10:18pm

Just curious (even after reading all benefits of pdf publishing), will it be a good idea to do an iBook too?  The demographics of ipad owners are not too small too and might be a good place to do. I played with iBook author a little and seems interesting due to its ability to add interactive elements. 

Permalink Reply by Amy on November 7, 2011 at 3:24pm

The fact that the book is published in PDF format offers new advertising opportunities: clickable banner ads. That would be the first time that pay-per-click or pay-per-lead advertising is sold in an e-book, and used to finance the cost of publishing the book.

Permalink Reply by Avijit Paul on February 13, 2012 at 10:34pm

While others point out the contents, may I add suggestions on style? 

After reading the articles it seems to me that short magazine style layout might suit. Here is one template we can probably use: 

http://graphicriver.net/item/24-page-indesign-magazine-a4/129724?WT...

Permalink Reply by Eric Flores on February 14, 2012 at 6:08am

PDF render beautiful electronic version of paper books or magazines. Still, they are optimized to be read on paper (or maybe a huge monitor while sitting on your desk).
However, electronic documents are best when consumed in a lightweigth ereader or tablet. Since these are smaller devices, in order to be able to fit a large font the book should reflow at the margin of this particular ereader. PDF is not appropriate for this use. EPub, and other proprietary ereader formats can reflow and are better suited for this purpose.

Permalink Reply by Vincent Granville on February 14, 2012 at 9:55am

Thanks for all the comments. I really need to work on the format, maybe hire someone since I don't have much time available (otherwise I would have used TEX rather than Word as word processor), also to proofread, optimize navigation, add structure to the book, an index etc.

The nice thing with PDF is that it has clickable links to the actual discussions, so you can access the most up-to-date versions of the discussions on AB, with all the fresh comments. But PDF takes lots of bandwidth and storage. Also the page size is too large. But it looks very nice when printed :-)

Permalink Reply by Vincent Granville on February 14, 2012 at 10:46am

Updated content as of 2/14/2012:

Introduction

Part I - Data Science Recipes

1. New random number generator: simple, strong and fast
2. Lifetime value of an e-mail blast: much longer than you think
3. Two great ideas to create a much better search engine
4. Identifying the number of clusters: finally a solution
5. Online advertising: a solution to optimize ad relevancy
6. Example of architecture for AaaS (Analytics as a Service)
7. Why and how to build a data dictionary for big data sets
8. Hidden decision trees: a modern scoring methodology
9. Scorecards: Logistic, Ridge and Logic Regression
10. Iterative Algorithm for Linear Regression
11. Approximate Solutions to Linear Regression Problems
12. Theorems for Traders
13. Preserving metric and score consistency over time and across clients
14. Advertising: reach and frequency mathematical formulas
15. Real Life Example of Text Mining to Detect Fraudulent Buyers
16. Discount optimization problem in retail analytics
17. Sales forecasts: how to improve accuracy while simplifying models?
18. How could Amazon increase sales by redefining relevancy?
19. How to build simple, accurate, data-driven, model-free confidence intervals
20. Comprehensive list of Excel errors, inaccuracies and use non-standard statistical definitions
21. 10+ Great Metrics and Strategies for Email Campaign Optimization

Part II - Data Science Discussions

1. Statisticians Have Large Role to Play in Web Analytics (AMSTAT interview)
2. Future of Web Analytics: Interview with Dr. Vincent Granville
3. Connecting with the Social Analytics Experts
4. Interesting note and questions on mathematical patents
5. Big data versus smart data: who will win?
6. Creativity vs. Analytics: Are These Two Skills Incompatible?
7. Barriers to hiring analytic people
8. Salary report for selected analytical job titles
9. Are we detailed-oriented or do we think "big picture", or both?
10. Why you should stay away from the stock market
11. Gartner Executive Programs' Worldwide Survey of More Than 2,300 CIOs
12. Analysts Explore Cloud Analytics at Gartner Business Intelligence Summit 2012
13. One Third of Organizations Plan to Use Cloud Offerings to Augment BI Capabilities
14. Twenty Questions about Big Data and Data Sciences
15. Interview with Drew Rockwell, CEO of Lavastorm

Part III - Data Science Resources

1. Vincent’s list

Permalink Reply by Joseph Terrell on April 18, 2012 at 4:29am

Excellent reference and thank you for making it available. My company is caught right at Part II Section 6. We are a very creative software company that are focused on analytics of big data in real time, however we lack the analytic know how. We think our technology is interesting based on discussions we have had by offering true real-time (getting answers as they happen) but turing technology into a product and understanding what is important as a product is very difficult. You work here has really inspired me and has helped me quite a bit.

Thanks!