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Book Description
Data warehouseing is key information management strategy for businesses that want to stay competitive into the next century. With this practical, information-packed sourcebook enterprise computing professionals will discover how to design and build an effective data warehousing system. Author Rob Mattison provides a well-organized, step-by-step plan and offers a valuable, vendor-independent examination of the available tools and products. He explains the key concepts of business process reengineering, client/server technology, systems architecture, online analytical processing (OLAP), and decision support systems (DS) that are critical to data warehousing. Synopsis
With this practical, information-packed sourcebook, enterprise computing professionals will discover how to design and build an effective data warehousing system. Mattison provides a step-by-step plan and offers a valuable, vendor-independent examination of the available tools and products. From the Back Cover
Maintain your company's competitive edge with a key information management strategy for the next millennium This pragmatic reference from a respected data and database management practioner gives you essential information and guidance on designing and building an effective data warehousing system. Even if you know next to nothing about data warehousing, this practical sourcebook gives you the tools, concepts, and approaches to tame your organization's vast stores of information. Author Rob Mattison explains what data warehouses are, how they work, and why the survival of many businesses in the twenty-first century will depend on leading-edge information architecture. At the heart of Data Warehousing, you'll find a logically organized, step-by-step plan for creating these next-generation decision support systems. Mattison explains the key concepts of business process reengineering, client/server technology, systems architecture, online analytical processing (OLAP), decision support systems (DDS), and other subjects crucial to effective data warehousing. Other topics include: Multidimensional analysis of stored data; Formatting, modeling, and synchronization of data; Statistical analysis; Neural networks; Data mining concepts and techniques; Legacy systems vs. data warehousing... .budgeting for and staffing the data warehouse, and more. You'll also read case studies of businesses that have implemented successful systems. Back to Data Warehousing
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