【正文】 由于兩系統(tǒng)提供的功能不一樣，需要不同類型的數(shù)據(jù)，因此需要維護分離的數(shù)據(jù)庫。決策支持系統(tǒng)需要歷史的數(shù)據(jù)，而操作數(shù)據(jù)庫一般不保存歷史數(shù)據(jù)。并行控制和恢復(fù)機制，比如鎖定和測量，都需要確保交易的一致性和穩(wěn)定性。另一方面，數(shù)據(jù)倉庫查詢通常是復(fù)雜的。然而，在線分析系統(tǒng)存儲大部分是只讀的，盡管大部分可以復(fù)雜查詢。在線分析系統(tǒng)同樣處理來自不同組織的數(shù)據(jù)，從大量數(shù)據(jù)存儲中整合信息。 （ 3）數(shù)據(jù)庫的設(shè)計：聯(lián)機處理系統(tǒng)通常采用實體數(shù)據(jù)模型和應(yīng)用聯(lián)機系統(tǒng)數(shù)據(jù)設(shè)計。在線分析系統(tǒng)是以市場為導(dǎo)向，用于知識工作者包括管理員、執(zhí)行官和分析員處理數(shù)據(jù)。這種系統(tǒng)可以用不同的格式組織和提供數(shù)據(jù)，以便滿足不同用戶的形形色色需求。 聯(lián)機操作數(shù)據(jù)庫系統(tǒng)的主要任務(wù)是執(zhí)行聯(lián)機事務(wù)和查詢處理。在數(shù)據(jù)倉庫中進行的查詢處理并不影響在局部源上進行的處理。數(shù)據(jù)倉庫使用更新驅(qū)動的方法，而不是查詢驅(qū)動的方法。由不同站點返回的結(jié)果被集成為全局回答。 對于異種數(shù)據(jù)庫的集成，傳統(tǒng)的數(shù)據(jù)庫做法是：在多個異種數(shù)據(jù)庫上，建立一個包裝程序和一個集成程序（或仲裁程序）。 從異種數(shù)據(jù)庫集成的角度看，數(shù)據(jù)倉庫也是十分有用的。有些人使用術(shù)語“建立數(shù)據(jù)庫”表 示構(gòu)造數(shù)據(jù)倉庫的過程，用倉庫 DBMS 表示管理和使用數(shù)據(jù)倉庫?！? 基于以上所講的，我們把數(shù)據(jù)倉庫視為構(gòu)造和使用數(shù)據(jù)倉庫的過程。它通常只需要兩種數(shù)據(jù)訪問：數(shù)據(jù)的初使化裝入和數(shù)據(jù)訪問。數(shù)據(jù)清理和數(shù)據(jù)集成技術(shù)被運用于確保命名的合理性、代碼的結(jié)構(gòu)，結(jié)構(gòu)尺度等。 (1)面向?qū)ο螅簲?shù)據(jù)倉庫是圍繞一些主題，如顧客、供應(yīng)商、產(chǎn)品和銷售組織。 按照 Inmon,一位數(shù)據(jù)倉庫構(gòu)造方面的領(lǐng)頭建筑師說，“數(shù)據(jù)倉庫是一個面向主題的、集成的、隨時間變化的、非易失的數(shù)據(jù)的集合，支持管理決策制定。許多人也認為隨著競爭加劇，數(shù)據(jù)倉庫己成為營銷必備的手段 —— 一種了解顧客的需求的武器。s decision making process. This short, but prehensive definition presents the major features of a data warehouse. The four keywords, subjectoriented, integrated, timevariant, and nonvolatile, distinguish data warehouses from other data repository systems, such as relational database systems, transaction processing systems, and file systems. Let39。 1 DATA WAREHOUSE Data warehousing provides architectures and tools for business executives to systematically anize, understand, and use their data to make strategic decisions. A large number of anizations have found that data warehouse systems are valuable tools in today39。s take a closer look at each of these key features. (1)Subjectoriented: A data warehouse is anized around major subjects, such as customer, vendor, product, and sales. Rather than concentrating on the daytoday operations and transaction processing of an anization, a data warehouse focuses on the modeling and analysis of data for decision makers. Hence, data warehouses typically provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process. (2)Integrated: A data warehouse is usually constructed by integrating multiple heterogeneous sources, such as relational databases, flat files, and online transaction records. Data cleaning and data integration techniques are applied to ensure consistency in naming conventions, encoding structures, attribute measures, and so on.. (3)Timevariant: Data are stored to provide information from a historical perspective (., the past 510 years). Every key structure in the data warehouse contains, either implicitly or explicitly, an element of time. (4)Nonvolatile: A data warehouse is always a physically separate store of data transformed from the application data found in the operational environment. Due to this separation, a data warehouse does not require transaction processing, recovery, and concurrency control mechanisms. It usually requires only two operations in data accessing: initial loading of data and access of data.. In sum, a data warehouse is a semantically consistent data store that serves as a physical implementation of a decision support data model and stores the information on which an enterprise needs to make strategic decisions. A data warehouse is also often viewed as an architecture, constructed by integrating dat