UPDATED- Here are three great examples of a visualization making a process easy to understand. Please click on the images to read them clearly.
1) It visualizes CRISP-DM and is made by Nicole Leaper (http://exde.wordpress.com/2009/03/13/a-visual-guide-to-crisp-dm-methodology/)
2) KDD -Knowledge Discovery in Databases -visualization by Fayyad whom I have interviewed here at http://www.decisionstats.com/interview-dr-usama-fayyad-founder-open-insights-llc/
and work By Gregory Piatetsky Shapiro interviewed by this website here
3) I am also attaching a visual representation of SEMMA from http://www.dataprix.net/en/blogs/respinosamilla/theory-data-mining
I recently read a review copy of Dr Eric Siegel’s new book Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
(Disclaimer-I have interviewed Eric here in September 2009, and we have been in touch over the years as his Predictive Analytics Conference became a blog partner and then a sponsor here at Decisionstats.com PAWCON also took off, becoming the biggest brand in independent analytics conferences)
So it was with a slight note of optimism that I opened this book, and it has so far exceeded my expectations. This is a very lucidly writtern, well explained book that can help people at all levels for analytics. There is a wealth of information here in a wide variety of business domains, and the beautifully designed book also has great tables, examples, and quotes, cartoons to make a very readable case for predictive analytics. Of course, Eric has some views, he loves ensemble modeling, conversion uplift models, privacy concerns, and his background in academics help explain even technical things very elaborately and in an interesting manner.
And at $14,6 it is quite a steal from Amazon. So buy a copy and read it. I would recommend it for helping build a case for predictive analytics , evangelizing to clients, and even to students in grad school programs. This is how analytics books should be , easy to read, and lucid to remember and practical to execute!
It all started because of the Google Guy, Hal Varian
|Feb 25, 2009 – I keep saying the sexy job in the next ten years will be statisticians. … Hal Varian, The McKinsey Quarterly, January 2009. …
Then these guys ( Thomas H. Davenport and D.J. Patil) made us sexy -that too in the Harvard Business Review.
Jill Dyche* is a thought leader. That’s what her job says. that too at SAS which took over her start-up Baseline Consulting. (* In addition to this, she writes forewords for struggling poets here )
She says here–
If the importance of data scientists is growing with the advent of big data, the sooner we understand what exactly it is they do, the better.
That is fair enough. But to add grievous injury to data scientists, She adds
(For fun I wrote a blog post on being a data scientist’s girlfriend.)
Actually the blog post was-Why I Wouldn’t Have Sex with a Data Scientist
But there’s no use. The data scientist is preoccupied. Preoccupied with finding, accessing, analyzing, validating, cleansing, integrating, provisioning, modeling, verifying, and explaining data to his management, colleagues, end-users, and friends.
And this is the year of the statistician ??
This is bare knuckles tactics. The art of Vaseline Insulting? Perish the thought. Geeks and Data Scientists rule.
Dont we? and we are perfect? right.
We statisticians (and data scientists and big dataists and data miners and business analysts and …)
are bringing sexy back!
(and we need a hug too.)