Data warehousing is one of the hottest business topics, and there's more to understanding data warehousing technologies than you might think. Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. Data is probably your company's most important asset, so your data warehouse should serve your needs. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. You'll learn to: Analyze top-down and bottom-up data warehouse designs Understand the structure and technologies of data warehouses, operational data stores, and data marts Choose your project team and apply best development practices to your data warehousing projects Implement a data warehouse, step by step, and involve end-users in the process Review and upgrade existing data storage to make it serve your needs Comprehend OLAP, column-wise databases, hardware assisted databases, and middleware Use data mining intelligently and find what you need Make informed choices about consultants and data warehousing products Data Warehousing For Dummies, 2nd Edition also shows you how to involve users in the testing process and gain valuable feedback, what it takes to successfully manage a data warehouse project, and how to tell if your project is on track. You'll find it's the most useful source of data on the topic!
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There's more to data warehousing than you think, so start right here!
You don't need a forklift to work with a data warehouse, but you do need a hefty load of know-how to make wise decisions when setting one up. Data is probably your company's most important asset, so your data warehouse should serve your needs. Here's how to understand, develop, implement, and use data warehouses, plus a sneak peek into their future.
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Making data warehousing understandable to readers, this revised edition provides need-to-know information about the structure, interrelationships, and technologies of data warehouses. It reviews the strengths and weaknesses of the top-down and bottom-up data warehousing approaches, and methods for capturing metadata for master data management. It offers a clear - and even irreverent - explanation of how data warehouses interact with tools for data visualization, online analytical processing, data mining, and business intelligence. It walks readers step by step through the process of building a team, capturing requirements, analyzing data stores, and involving end users in the process.
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