A to Z of Big Data

This post from +Big Data Made Simple tries to list all the terms use in Big Data.

I'm partly surprised how much I understood but also partly dismayed at all the term I still don't understand.

Big Data Myths Busted

In this insightful article by Matt Beck at FICO he goes through some traditional Marketing wisdom and discusses if they are valid or not.

Putting Big Data into Practice

Here is what was discussed at the Computing IT Leaders Forum.

I have to agree that it is imperative get something up, running and providing results in weeks rather than months.  It's a big investment in time and resources and needs to show reasons for why it s there and should remain.

Two different views of the recent news about experiments with users at Facebook

This news article is about the Data Science team at Facebook and is from the +Wall Street Journal. It was written by +Reed Albergotti.

This news article is also about the recent experiments with customers at Facebook and is from the +Wall Street Journal.  It was written by +Farhad Manjoo.

I have to admit to feeling slightly disturbed by their experimenting with real people (maybe even with me) but also envious of them having such a large a rich source of data with the time to do analyses to see what it can tell them.

10 books to get you started with Hadoop

In +Big Data Made Simple there is an article listing the 10 books you should read to get you started with Hadoop.

A good place to start you education :-)

How companies use R to compete in a data driven world

This article from +Data Informed written by +David Smith talks about the number of organisation that are not using R in their data related activities.

R is increasingly important and can now be used with Teradata as shown in this article also from +Data Informed.

I'm so pleased I can code in R even if it is quite simply.

Converting Numerical Data to Categorical Data

In this article in MSDN Magazine James McCaffrey goes through a coded example in C# of how to automate converting numerical data to categories.  I think you culd convert it to another language fairly easily.

In his wrap up he talks about setting a maximum of the number of categories.  I think that is crucial because if you have too many then it's going to be difficult to understand results using the categories.