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SmartData Collective > Big Data > Data Warehousing > In-Database analytics: Teradata and SAS lead in speed by ‘thinking inside the box’
Data WarehousingPredictive Analytics

In-Database analytics: Teradata and SAS lead in speed by ‘thinking inside the box’

DarrylMcDonald
Last updated: 2009/11/11 at 8:08 PM
DarrylMcDonald
5 Min Read
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In-database-analyticsToo many companies think slow — outside the data warehouse box — when it comes to advanced analytics. Despite the consensus that analytics must be operationalized to reap full value and benefit, most companies are still dealing with excessive data management, movement, redundancy, and complexity – leading to best case tedious processes that take far too much time and cost in today’s environment and worst case to average conclusions leading to average business decisions

Today, it pays to think, move and act fast… really fast, which means thinking inside the box, analyzing analytics models inside the database. On this topic, two press releases issued just days ago from the Teradata-SAS partnership have huge implications for every company that competes on analytics.

  • With the new releases of Teradata 13 and SAS 9.2, several key SAS procedures can execute in Teradata – further expanding the world’s best value proposition for accelerating queries and delivering maximum analytic performance.
  • SAS and Teradata continue to build our joint customer base: over 350 engagements in 24 months, and growing. The partnership has a strong lead over other vendors in this space who recently …



In-database-analyticsToo many companies think slow — outside the data warehouse box — when it comes to advanced analytics. Despite the consensus that analytics must be operationalized to reap full value and benefit, most companies are still dealing with excessive data management, movement, redundancy, and complexity – leading to best case tedious processes that take far too much time and cost in today’s environment and worst case to average conclusions leading to average business decisions

More Read

First Look – SAS In-Database Analytics

Data Glut? The Answer Is Innovation
Innovation + Affordability = Enterprise Intelligence

Today, it pays to think, move and act fast… really fast, which means thinking inside the box, analyzing analytics models inside the database. On this topic, two press releases issued just days ago from the Teradata-SAS partnership have huge implications for every company that competes on analytics.

  • With the new releases of Teradata 13 and SAS 9.2, several key SAS procedures can execute in Teradata – further expanding the world’s best value proposition for accelerating queries and delivering maximum analytic performance.
  • SAS and Teradata continue to build our joint customer base: over 350 engagements in 24 months, and growing. The partnership has a strong lead over other vendors in this space who recently have attempted to make “just as good as claims” about their new in-database capabilities.
  • The new SAS-Teradata analytic think tank with Elder Research will provide companies with unmatched resources – real, live, cutting edge analytics leaders – to advise on brilliant new approaches and opportunities in data mining. In the Business Analytics Innovation Center, companies will learn how to make new inferences from currently unknown facts and quantify and score underlying critical future trends or patterns in their business that today go unnoticed. The Center will have a visionary lab for pilot programs, analytic workshops, and proofs of concept for prospective customers.

Thinking inside the box: it’s becoming a source of higher intelligence and competitive advantage. But don’t just take my word for it. Read what a leading IT firm has said in the Forrester Research teleconference, In-Database Analytics: Transforming The Data Warehouse Into The New Analytic Application Server, hosted by senior analyst James Kobielus:

“In-database analytics has a strong return on investment and the Enterprise Data Warehouse (EDW) is an optimal platform for in-database analytics as a reusable application. In-database analytics cuts costs by allowing data mining specialists to consolidate analytical data marts into the EDW, reduces bandwidth utilization by eliminating the need to move massive analytical data sets to and from EDW, and shortens time to build, execute, deploy, and optimize predictive models by leveraging EDW horsepower.”

James’ words, not mine – but I couldn’t have said it better. The point: when your business needs high intelligence delivered at the speed of light, it’s time to start thinking inside the box.

 

Darryl McDonald 
 

TAGGED: in-database analytics, teradata 13
DarrylMcDonald November 11, 2009
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