Added by Michael Walker on September 26, 2012 at 10:00am — No Comments
The goal of Data Analytics (big and small) is to get actionable insights resulting in smarter decisions and better business outcomes. How you architect business technologies and design data analytics processes to get valuable, actionable insights varies.
It is critical to design and build a data warehouse / business intelligence…
Added by Michael Walker on September 19, 2012 at 11:57am — No Comments
The goal is to design and build a data warehouse / business intelligence (BI) architecture that provides a flexible, multi-faceted analytical ecosystem for each unique organization.
A traditional BI architecture has analytical processing first pass through a data warehouse.
In the new, modern BI architecture, data reaches users…Continue
Added by Michael Walker on September 12, 2012 at 11:53am — No Comments
Copyright © SAS Institute Inc., Cary, NC, USA. All Rights Reserved. Used with permission.
Optimization answers the question: How do we do things better? What is the…Continue
Companies, products, and technologies included in the Big Data Landscape:
Added by Michael Walker on August 30, 2012 at 2:58pm — No Comments
The Hadoop stack includes more than a dozen components, or subprojects, that are complex to deploy and manage. Installation, configuration and production deployment at scale is challenging.
The main components…Continue
Added by Michael Walker on August 22, 2012 at 9:40am — No Comments
Today Analytics is the heart of a Business. Companies are challenged with a high volume and broad array of data which requires active and effective analysis. Analysis can help them make enhanced and improved business decisions, and hence help the business to maintain profitability. "Companies need to compete on the basis of key business processes, and how they optimize these processes with analytics," says Thomas Davenport, professor and director of research, Babson College, USA. Business…Continue
Added by AcademyForDecisionScience&Analyt on August 16, 2012 at 1:40am — No Comments
A Big Data decision support system requires particular capabilities in terms of volume, variety of data and processing speed.
Today companies to improve their knowledge models and forecasts, do not hesitate to take into account hundreds of factors, and do not hesitate to bring up new means of analysis that can handle large volumes of data. But the processing of large volumes of data is a challenge for traditional BI infrastructure. Storing large volumes is not a problem, but…
Added by Michel Bruley on July 31, 2012 at 11:03pm — No Comments