Mon premier blog

Too Big to Ignore: The Business Case for Big Data by Phil Simon

Too Big to Ignore: The Business Case for Big Data Phil Simon ebook
Page: 256
Publisher: Wiley
Format: pdf
ISBN: 9781118638170

In addition, Columbus recently enjoyed the announcement of a major “Big Data” project involving at least 500 high-wage jobs from IBM. Yes, we've all heard of Big Data, perhaps even read about it. There is no indication that State Farm Insurance is actually . Feb 1, 2013 - How Some Locations are Making Their Business Case for Incentives . Aug 30, 2013 - Author Phil Simon presented the business case for big data from a big picture perspective, but I think that I would have gotten more from the book if I had a better background in some of the technical issues presented. Mar 6, 2014 - There was a great passage in Alexis Madrigal's recent interview with Gibu Thomas, who runs innovation at Walmart: Our philosophy is pretty simple: When we use data, be transparent In some ways, the worst case scenario in the last paragraph above is tinfoil hat stuff. For more on the conference, click here. There are far too many creepy business and government data collection practices for that to be a true statement. Aug 22, 2013 - Big Data has been declared the “sexiest job of the 21st century” and it's already reshaping corporate decisionmaking and even talent recruitment. Feb 22, 2011 - Attendees will receive a copy of Too Big to Ignore and I'll be signing copies after my talk. Mar 29, 2013 - If it conjures up any image at all, it's pages of numbers and text with a vague bearing upon business reality. The City of Columbus granted a 65 percent income tax credit as well as an annual cash Add in a state of Ohio Job Creation Tax Credit of 60 percent over eight years, and the incentives are just too big for corporations to ignore. Apr 3, 2013 - I think many will feel the same way reading Phil Simon's new book, Too Big to Ignore: The Business Case for Big Data. Jun 7, 2013 - In this post I will attempt to explain these terms from the perspective of a traditional database practitioner but getting wet on the Big Data issues by being thrown in the water.