Data Veracity, uncertain or imprecise data, is often overlooked yet may be as important as the 3 V's of Big Data: Volume, Velocity and… Continue
Added by Michael Walker on November 28, 2012 at 3:00pm —
Join Fernando, Chief Technologist, Enterprise, for MarkLogic in a discussion on how to combine the power of Tableau™ against a NoSQL Database that is able to perform analytics against disparate data sets composed of structured, unstructured and graph data. The result is an unprecedented level of flexibility and power from being able to correlate and analyze “Big Ugly Data” in its natural form. The use case will… Continue
Added by Vincent Granville on November 28, 2012 at 10:30am —
Along with several others, Harvard Business Review has recently pointed out an area with significant job growth which is appropriate for individuals with a curious nature and an expertise in business analytics. But who will dominate this area? The Data Scientist- trending as “the sexist job” in America, this role has a desirability that calls upon… Continue
Added by Ben Gold on November 28, 2012 at 6:36am —
Big data is the most talked term these days in the analytics world. It will have big transformative impact on all the aspects of the business.
Most of the companies now have realized that there is a huge competitive advantage in analyzing the humongous data quickly & effectively for future insights.
Big data analytics is the disruptive technology… Continue
Added by Sandeep Raut on November 24, 2012 at 6:12pm —
Top 50 data science / big data tools, described in less than 40 words, for decision makers. Please help us: any definition that you fill will have your name attached to it: send your definition or new term and definition to [email protected]… Continue
Added by Vincent Granville on November 24, 2012 at 1:30pm —
October 22, 2012
As some of you may know, StatSoft has launched a program to offer free Enterprise Business Analytics software to aid struggling companies in Greece, Portugal, and Spain with the intent to… Continue
Added by Vincent Granville on November 21, 2012 at 9:00am —
Added by Vincent Granville on November 18, 2012 at 5:00pm —
Here we go. Enjoy!
Added by Vincent Granville on November 17, 2012 at 2:30pm —
Transforming into a data-driven organization - turning information into actionable insights is a three (3 ) part strategy: Continue
• Technology – build a modern BI/DW architecture & analytics ecosystem with…
Added by Michael Walker on November 14, 2012 at 9:22am —
Big Data holds a big promise. But has that promise paid out already? Or are you heading for Big Dollar Disaster? Many take inventory of their data and find out they have terabytes of data lying around. Surely something should be done with that, so here’s how we see a lot of companies going about implementing ‘something’ for their Big Data.
- Buy hardware, set up a cluster and install some flavor of Hadoop.
- Break their brains to figure out how to run map-reduce…
Added by Jos Verwoerd on November 13, 2012 at 2:08am —
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Added by Zach Piester on November 13, 2012 at 1:00am —
How to use s3 (s3 native) as input / output for hadoop MapReduce job. In this tutorial we will first try to understand what is s3, difference between s3 and s3n and how to set s3n as Input and output for hadoop map reduce job. Configuring s3n as I/O may be useful for local map reduce jobs (ie MR run on local cluster), But It has significant importance when we run elastic map reduce job (ie when we run job on cloud). When we run job on cloud we need to specify storage location for input as… Continue
Added by Rahul Patodi on November 11, 2012 at 8:00am —
What is Hadoop: Hadoop
is a framework written in Java for running applications on large clusters of commodity hardware and incorporates features similar to those of the Google File System and of MapReduce. HDFS is a highly fault-tolerant distributed file system and like…
Added by Rahul Patodi on November 11, 2012 at 8:00am —
When creating a predictive model, data miners need to “tune” it to make the right kind of mistakes. Setting the cut-off point between ‘promising’ and ‘unpromising’ depends a lot on our client’s biggest concern -- missed opportunities or false alarms.
Data Mining Misconceptions #1: The 50/50 Problem…
Added by Daniel R. Graettinger on November 8, 2012 at 5:00pm —
Jim Meyerle is co-founder and EVP of Strategy and Finance forEvolv On-Demand.…
Added by Vincent Granville on November 8, 2012 at 1:49pm —
Predicting election results in the 50 states is actually much more easy than most people think. West Coast and East Coast are democrat, Midwest, Texas etc. are mostly republican (the Midwest becoming more republican because the population is aging due to brain drain by young, smart people - mostly democrats). So indeed the task is not about correctly predicting results for the 50 states, but simply predicting… Continue
Added by Vincent Granville on November 8, 2012 at 11:00am —
There is little time, about 3 or 4 years, if you wanted to process a large amount of textual data or web logs, you need to mobilize large servers and implement consistent SQL programs, long to be developed long and long to give results. Fortunately requests were few and generally volumes were measured at most in terabytes. Now e-commerce and social media have been largely developed, and many companies see their customer relationships, and therefore their survival, entirely dependent on the… Continue
Added by Michel Bruley on November 8, 2012 at 3:58am —
Hadoop (MapReduce where code is turned into map and reduce jobs, and Hadoop runs the jobs) is the most well known technology used for "Big Data" because it allows an organization to store huge quantities of data at very low… Continue
Added by Michael Walker on November 7, 2012 at 3:57pm —
Initiating the LPG (Liberalization, Privatization, and Globalization) policies, the consumer behaviour is also changed drastically with their preferences and choices of the products available in the market. Consumers are demanding Global Products at Local Markets. Consumer Point of View (40-60% of the total consumer’s of the economy or total population), with available time if he found more products available (all different products at one place), he will ready to pay higher prices. Retail… Continue
Added by Vijay Kumar on November 4, 2012 at 12:41am —
Feature selection, also known as variable selection, feature reduction, attribute selection or variable subset selection is the technique of selecting a subset of relevant features for building robust learning models (Source: Wikipedia). Data mining problems may involve hundreds, or even thousands, of variables that can potentially be used as inputs. As a result, a great deal of time and effort may be spent examining which variables to include in the model. Feature selection allows us to… Continue
Added by Venky Rao on November 3, 2012 at 10:03pm —