Building Business Intelligence Applications with .NET
Rob Ericsson
- 出版商: Charles River Media
- 出版日期: 2004-02-25
- 售價: $1,320
- 語言: 英文
- 頁數: 350
- 裝訂: Paperback
- ISBN: 1584502711
- ISBN-13: 9781584502715
-
相關分類:
.NET
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商品描述
Businesses generate a tremendous amount of data from everyday transactions that needs to be processed and analyzed quickly. Business Intelligence (BI) applications make this possible; however, these applications are often very complex, making it difficult for companies to use off-the-shelf tools. Therefore, many BI applications are customized in house. In fact, a recent survey by The Data Warehousing Institute found that 62% of companies develop BI applications internally. BI is an area of growth in the IT environment, so the need for good development resources is high. Building Business Intelligence Applications with .NET provides such a resource by teaching corporate software developers how to use .NET technologies to build applications for data mining, statistical analysis, or OLAP, and integrate them with existing transactional applications. Data issues, analytical techniques, and flexibility have a more prominent position in business applications, and .NET offers compelling technologies (such as Web Services, Smart Clients, and XML for Analysis) that help developers construct BI applications.
FEATURES
- Teaches developers how to construct data mining, statistical analysis and
OLAP applications using .NET technologies such as Web Services, Smart Clients,
and XML for Analysis
- Explains how to construct business applications that allow your company to
produce insight through its transactional systems, not just numbers
- Helps developers make the transition from creating transactional
applications to BI applications
- Includes a CD-ROM with all of the source code from the book, as well as relevant standards documents (XML, Web services, etc.)
BRIEF TOC
Chapter 1: Business Intelligence; Chapter 2: The .NET Data Warehouse; Chapter 3: OLAP Cubes; Chapter 4: Analysis Service Clients; Chapter 5: XML for Analysis; Chapter 6: Reporting; Chapter 7: Data Mining; Chapter 7: Analytic Applications; Chapter 8: Knowledge Management; Appendix A: MDX Functions; Appendix B: MDX Properties; Appendix C: XMLA Rowsets; Appendix D: OLE DB for OLAP Schemas; Appendix E: MDX Operators; Glossary