Kimball CornerInformatica has teamed up with Dr. Ralph Kimball and the Kimball Group to provide you with the latest, most innovative information on data warehousing. Here's your one-stop shop for new data warehousing strategies, approaches, and techniques. Be sure to:
Dr. Ralph Kimball, founder of the Kimball Group, is known worldwide for his practical and innovative work in dimensional data warehousing. Since the mid 1980s, Dr. Kimball has been the data warehouse/business intelligence industry's thought leader on the dimensional approach and trained more than 10,000 IT professionals. He developed the Data Warehouse Toolkit series of books, the all-time best sellers in the field. He teaches dimensional data warehouse design for Kimball University and critiques data warehouse designs. Prior to working at Metaphor and founding Red Brick Systems, he co-invented the Star workstation at Xerox's Palo Alto Research Center (PARC). Dr. Kimball has a doctorate in electrical engineering from Stanford University.
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2011 WebinarsIn our popular Webinar series for 2011, Dr. Ralph Kimball discusses the emerging trends, challenges and opportunities that are impacting business intelligence and data warehousing professionals in a rapidly evolving data environment. Make Big Data Agile: Improve Reliability & Trustworthiness by Aligning Process & Data Evolve EDW to become Adaptable Infrastructure for Big Data Analytics Empower Agility by Getting Real about Data Virtualization Rethinking EDW in the Era of Expansive Information Management White PapersNEW in 2011! The Evolving Role of the Enterprise Data Warehouse in the Era of Big Data Analytics Essential Steps for the Integrated EDW Webinar replaysRealizing the Potential of a Data-Driven Enterprise EDW Best Practices for Behavior Analytics to Attract & Retain Customers Modernizing the Enterprise Data Warehouse Drive End-to-End Data Governance From Your Data Warehouse Foundation Reverse the Flow of Data Warehouse Design to Ensure Success The Enterprise Data Warehouse: The Platform for Pervasive BI Drive Data Quality with Metadata | ||