本书作为SAP BW的经典教材,内容详实丰富,适用于BW初学者和进阶用户。电子版方便携带与查阅,是每一位SAP从业者的必备参考书。
以下是根据你的要求处理后的文档内容:
**Introduction**
This document provides an overview of the architecture and functionality within SAP Business Information Warehouse (BW). It covers various aspects including data access, analysis services, administration procedures, performance planning strategies, and more. The content is organized into chapters that delve deeply into specific areas such as analytic applications, system setup considerations for optimal performance management.
**Chapter 1: Overview of the SAP BW Architecture**
This chapter introduces readers to the fundamental concepts behind SAP Business Information Warehouse (BW) architecture. It outlines key components like data extraction, transformation processes, and how information is stored within different objects types in BW environment.
**Chapter 2: Basic Concepts and Terminology for Data Warehousing**
Here we explore foundational terms commonly used in data warehousing contexts relevant to the operation of SAP Business Information Warehouse (BW). Understanding these concepts helps users navigate through technical discussions about BW functionalities more effectively.
**Chapter 3: Master Data Management**
This section focuses on managing master data within the context of SAP Business Information Warehouse. It includes strategies for handling and maintaining accurate, consistent master records which are crucial for reliable business analytics.
**Chapter 4: Transactional Data Extraction from Source Systems**
Details how transactional data is extracted efficiently from source systems to be utilized in BW processes. This involves setting up extraction jobs that ensure timely updates of information within the warehouse environment.
**Chapter 5: Information Modeling and Storage Structures**
Describes methodologies for designing efficient storage structures by creating optimized InfoObjects (like InfoCubes, ODS objects) based on business requirements. Proper modeling ensures fast retrieval times while maintaining data integrity across various analytical queries executed against these models.
**Chapter 6: Data Loading Techniques in SAP BW**
Explores different methods available to load both master and transactional datasets into the warehouse efficiently without compromising performance or accuracy of results generated from analyses performed thereupon.
**Chapter 7: Information Access, Analysis & Presentation Services**
Discusses tools and interfaces provided by SAP Business Information Warehouse (BW) that enable users to interact with data stored within it. This includes query design capabilities as well as advanced reporting features tailored towards facilitating insightful business intelligence outputs.
**Chapter 8: Analytic Applications in BW Environment**
Provides an insight into specialized analytic applications built on top of core functionalities offered by SAP Business Information Warehouse platform. These solutions cater specifically toward addressing complex analytical needs arising out of CRM, supply chain management or financial planning domains among others.
**Chapter 9: Administrative Tasks within the SAP BW System**
Covers essential administrative activities required to maintain optimal functioning and security measures in place for protecting sensitive corporate data residing inside business information warehouses managed via this platform.
**Chapter 10: Performance Planning & Management Strategies**
Offers guidance on how best approach planning stages aimed at ensuring smooth running operations of large scale enterprise level BW installations while minimizing potential bottlenecks that could arise due to improper sizing decisions or misconfigured system parameters.
**Bibliography**
*Books*
[Listed books relevant for understanding SAP Business Information Warehouse]
*Papers and Articles*
[Collection of scholarly articles providing deeper insights into specific aspects discussed throughout the document.]
*Standards and Internet Resources*
[Sites offering technical guidelines, best practices documents related to data warehousing technologies including those supported by SAP.]