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TDWI Best Practices Report | Integrating Hadoop into Business Intelligence and Data Warehousing
Posted in: Business Intelligence - Apr 01, 2013Hadoop promises to assist with the toughest challenges in BI today, including big data, advanced analytics, and multi-structured data. Download this TDWI Best Practices Report to learn how to integrate Hadoop into your business intelligence, analytics, data integration, and data warehousing technology stacks.top
Executive Summary: Integrating Hadoop into Business Intelligence and Data Warehousing
Posted in: Business Intelligence - Apr 01, 2013Hadoop promises to assist with the toughest challenges in BI today, including big data, advanced analytics, and multi-structured data. Download this TDWI Best Practices Report to learn how to integrate Hadoop into your business intelligence, analytics, data integration, and data warehousing technology stacks.top
Business Intelligence and Analytics Fundamentals
Posted in: Business Intelligence - Mar 29, 2013The demands of business in today's economically challenging environment are forcing organizations to become smarter and more efficient about the use of their information. This paper from Ovum Research examines the key criteria and considerations you need to be aware of when evaluating your organization's BI and analytics strategy.top
Seven Steps for Implementing Data Discovery Tools
Posted in: Business Intelligence - Mar 28, 2013Expectations for what business intelligence needs to deliver are changing fast. At one time, BI technology demanded that users overcome steep learning curves, backlogs for applications, delays for batch queries, limited historical data, and static reports. Now users expect more. Tools and technologies are rapidly evolving to satisfy greater demands for ease of use, timely data access, and deeper analytics.top
Seven Steps for Implementing Data Discovery Tools
Posted in: Business Intelligence - Mar 28, 2013Expectations for what business intelligence needs to deliver are changing fast. At one time, BI technology demanded that users overcome steep learning curves, backlogs for applications, delays for batch queries, limited historical data, and static reports. Now users expect more. Tools and technologies are rapidly evolving to satisfy greater demands for ease of use, timely data access, and deeper analytics.top
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