The mantra is famous in Hollywood history: "Lions, and Tigers, and Bears. Oh my!" It brought fear to young viewers everywhere. But, as the story goes, it was soon obvious that there was nothing to fear.
With so much Big Data noise, and hype, and pressure (oh my!) pressing in on us from all sides, there is understandable fear and loathing around the concept of Big Data. In my opinion, the way to relieve any such concern is to address it objectively. And the way to do that is through a scientific approach -- i.e., through Data Science and the scientific application of Analytics.
With that in mind, and as a resource for anyone interested in further reading, I recently posted here 2 lists of books:
There is one more book that deserves special attention (to readers here), and that is Vincent Granville's upcoming Data Science book -- check out the awesome content here: Developing Analytic Talent - Becoming a Data Scientist.
The Wiley publishers' website gives this additional information:
The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one.
We are looking forward to the publication and release of this book in March 2014. It will provide a thorough resource for Big Data practitioners seeking information on Data Science, Analytics, and Machine Learning. Oh my!