Michael Vizard explains that current IT culture is used to giving people access to only a finite amount of data. But new data management frameworks such as MapReduce and Hadoop make it possible to cost-effectively analyze large amounts of data. Many IT organizations don’t have the skills in place to master those technologies. This gap […]
5 Misconceptions About Visualization
October 7, 2011 by Leave a Comment
Nathan Yau, the force behind the visual data site Flowingdata.com, wants data flow to be understandable for non-experts. He recently advised departments at the Census Bureau on how to visualize their data. While some people “got it,” others were laboring under some common misconceptions about effective presentation, software tools, layering of information, the myths of bias […]
In-Memory Analytics to Completely Disrupt Data Warehousing
October 4, 2011 by Leave a Comment
Timo Elliot of SAP’s Business Objects team puts forward an entertaining and persuasive argument that in-memory analytics, along with massively parallel hardware, column stores, and in-database analytics, are the same kind of disruptive innovation for traditional data warehouses as digital photography was to film cameras. Digital photography transformed an industry by eliminating obsolete layers. In-memory […]
Whitepaper: Building Data Science Teams
October 3, 2011 by Leave a Comment
How do you build a ‘data driven’ organization? How can existing firms be transformed into data driven juggernauts? DJ Patil, former Head of Analytics and Data Teams at LinkedIN and currently a Data Science in Residence at Greylock Partners, has written a white paper outlining how analytics operations are designed, what they do, the tools […]
10 Essential Elements of Data Mining
October 2, 2011 by Leave a Comment
Is Data Mining simply another name for Statistics, Business Intelligence, or Business Analytics? Not according to Keith McCormick, an independent Data Mining consultant and trainer. Data Mining has its own unique characteristics and McCormick comes up with a list of 10 elements that differentiate Data Mining from other strategies. Data Mining is not an unfocused […]
Inside BigData: Sports Roundup By the Numbers
September 30, 2011 by Leave a Comment
Here at inside-BigData, we’re not that different from everyone else: We like our sports. But we are a little geekish (no surprise there), so we enjoy exploring the numbers behind the sports. We’ve got three articles to share: “Big Data Analytics Versus Your Own Lying Eyes” discusses how analytics has finally hit Hollywood with “Moneyball,” […]
SAS Analytics Drives Kelly Blue Book In New Direction
September 27, 2011 by Leave a Comment
SAS Analytics software has given Kelly Blue Book the resources to transform Big Data into unrivaled insights for the automotive marketplace. The premier source of new- and used-car information created an enterprise analytic center of excellence – expanding from one employee to 23 in just three years – that improved decision making and helped the […]
Can Big Data Bring Business and IT Together?
September 26, 2011 by Leave a Comment
Gary Cokins wonders if the analytics trend could remove the traditional corporate wall between “The Business” and the IT organization. Referencing a provocative article by Jim Harris, Cokins argues that the more the business side relies on data analytics the more collaborative the relationship with IT must be. Today’s flood of data not only answers […]
Data Management at Zynga
September 24, 2011 by Leave a Comment
Curt Monash recently attended a “bit of a bash” with, among others, Ken Rudin of Zynga, the social gaming company. Of particular interest was Zynga’s approach to analytic database design: Data is divided into two parts. One part has a pretty ordinary schema; the other is just stored as a huge list of name-value pairs. (This […]
Video: Stephen Gold of IBM Talks Up Careers in Predictive Analytics
September 23, 2011 by Leave a Comment
This pep talk by IBM’s Stephen Gold, business line executive in charge of the company’s SPSS unit, is required back to school viewing for anyone who is considering a career in predictive analytics. He discusses the value of having skills in predictive analytics and the increased demand for such skills by employers around the globe. […]
