Microsoft(r) Data Warehousing: Building Distributed Decision Support Systems
by Robert S. Craig, Joseph A. Vivona, David Berkovitch
Category: Computers

Microsoft(r) Data Warehousing, Building Distributed Decision Support Systems, Robert S. Craig Joseph A. Vivona, David Bercovitch. Foreword by Judith Hurwitz, Robert S. Craig, Joseph A. Vivona, David Bercovitch. Foreword by Judith Hurwitz, SQL Server 7.0's exciting new features and components make it the data warehousing tool par excellence. In Microsoft Data Warehousing, experts Robert Craig, Joseph Vivona, and David Bercovitch show database administrators and developers how to use Microsoft's new generation of powerful DSS technologies to create dynamic, highly scalable data marts and warehouses tailored to their companies' current and future decision support requirements. In the first part of the book, the authors provide a detailed description of the data warehouse process based on the five environments that make up an integrated DSS. In Part II, they acquaint you with SQL Server 7.0 components and related Microsoft tools and then show you, step-by-step, how to best utilize them to design, develop, implement, and manage a multi-tier distributed decision-support application within each environment. You get detailed hands-on guidance for: * Data extraction processes and tools. * How to define the most appropriate decision support architecture. * Different DSS tools for the Desktop including EIS, Data Mining, Extended Reporting, and Managed Query. * Configuring SQL Server 7.0 for implementation, table definition, indexing strategies, query processing, and managing and enhancing performance. * The role of Microsoft Repository in design, development, and management and its support of UML. * How to achieve integration across the environments with OLE DB for OLAP and its key APIs. * Client access using Excel, Visual Basic, Java, English Query, and other query and analysis tools with SQL Server 7.0. * How to leverage the data in the data warehouse once it's built with various analysis scenarios such as customer relationship management, market basket, and market share.