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How to Develop a Sustainable Data Integration Plan for Business Intelligence Projects
sponsored by SAS Institute Inc.

A sound, sustainable data integration strategy is required for most business intelligence (BI) initiatives, since effective enterprise-wide BI analyzes information from many different source systems. But data integration for BI initiatives certainly isn't a one-time project. It's a set of ongoing processes that must work consistently and successfully every time, because errors can lead to flawed analysis, distrust in the system or worse, inaccurate corporate reporting.

In this podcast get expert advice from William McKnight, Sr. VP of Conversion Services International, Inc. on developing a sustainable BI-data integration strategy including:

  • Find out the unique data integration considerations for BI systems -- and learn why designing a BI-data integration strategy is different than some other data integration projects
  • Get more information about emerging real-time data integration methods, as well as other new tools and best practices that can support your efforts
  • Learn the most common mistakes organizations have made when designing BI-data integration strategies -- and find out how to avoid these common traps
  • Hear expert advice for designing BI-data integration strategies that are flexible, adaptable and sustainable for the long-haul
  • And more...
(THIS RESOURCE IS NO LONGER AVAILABLE.)
 
Available Resources from SAS Institute Inc.
sponsored by SAS Institute Inc.

WHITE PAPER - Let it be stated plainly: Business analytics are the key to achieving these challenging objectives. Our world generated more data in 2009 than in the previous recorded history of mankind. A good deal of this data can be converted into useful information and competitive advantage – by applying the right analytics.
Posted: 30 Jul 2010 | Published: 30 Jul 2010


sponsored by SAS Institute Inc.

WHITE PAPER - What exactly is business analytics and how can it help? Business analytics is, simply put, the application of analytical techniques to resolve business issues. It provides organizations with a framework for decision making, helping organizations solve complex business problems and more.
Posted: 30 Jul 2010 | Published: 30 Jul 2010


sponsored by SAS Institute Inc.

WHITE PAPER - We are now exiting a historical moment of under managed and only occasionally acted-upon information to an environment requiring much more active, much more intense, much more aggressive information management. You as an executive will be held much more accountable for your data management behaviors. Read this white paper to learn more.
Posted: 30 Jul 2010 | Published: 30 Jul 2010


sponsored by SAS Institute Inc.

WHITE PAPER - In their latest book, Thomas Davenport, Jeanne Harris and Robert Morison show how companies apply analytics in their daily operations. We see examples of analytics at work within core processes in a variety of business areas. Read this white paper to learn how embedding analytics into your organization's processes can help you.
Posted: 30 Jul 2010 | Published: 30 Jul 2010


sponsored by SAS Institute Inc.

WHITE PAPER - There are many ways to use analytics to improve an organization's effectiveness and efficiency, and many different ways to apply analytics. This report is about how to use analytics to improve day-to-day business operations.
Posted: 29 Jul 2010 | Published: 29 Jul 2010


sponsored by SAS Institute Inc.

WHITE PAPER - Leading banks use business analytics to predict and prevent credit fraud, saving millions. Retailers use business analytics to predict the best location for stores and how to stock them. But these advanced business applications tell only part of the story. What's going on inside these market-leading companies that sets them apart?
Posted: 29 Jul 2010 | Published: 29 Jul 2010


sponsored by SAS Institute Inc.

WHITE PAPER - This checklist lists and explains data requirements that are unique to advanced analytics. This report focuses on the data requirements of advanced analytics so organizations may become better equipped to populate a data warehouse or analytic database with data and data models that ensure the success of advanced analytic applications.
Posted: 07 Apr 2010 | Published: 07 Apr 2010


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