外文翻譯---信息系統(tǒng)的業(yè)務趨勢和后果

1、<p><b>　　附件：譯文</b></p><p>　　信息系統(tǒng)的業(yè)務趨勢和后果</p><p>　　到目前為止，實施典型數(shù)據(jù)處理系統(tǒng)的目標主要在于加快各個業(yè)務領域的發(fā)展速度、降低成本和使流程自動化。目前，企業(yè)資源規(guī)劃 (ERP) 系統(tǒng)和其他軟件工具的作用就是為大多數(shù)公司實現(xiàn)這些目標。結(jié)果，這些 ERP系統(tǒng)、客戶關系管理 (CRM) 系統(tǒng)、銀行和信用卡系

2、統(tǒng)以及公司管理規(guī)定使需要分析的數(shù)據(jù)量呈指數(shù)增長。有些公司認為這是負面影響；而另一些公司，如 SAP，卻將這巨大的電子信息量看作是一大筆財富。同樣的，隨著不斷增長的全球化發(fā)展和日益增加的分散經(jīng)營模式，認清市場趨勢和收集競爭者信息已成為一大需求。這允許公司迅速地應對市場條件的變化。你可以看出在這個網(wǎng)絡時代，有效的信息處理已成為在競爭者間維持優(yōu)勢的決定性因素。</p><p>　　現(xiàn)代化全球經(jīng)營企業(yè)里的決策者常常會意識

3、到他們的生存取決于信息的有效使用。遺憾的是，此信息通常分布于許多系統(tǒng)，有時甚至分布于許多國家，從而使信息的有效使用變得極其困難。而這恰恰是現(xiàn)代商務智能（BI）系統(tǒng)試圖應對的挑戰(zhàn)。若要涵蓋從源數(shù)據(jù)檢索到分析的整個流程，則需要廣泛的解決方案。各企業(yè)必須關注整個企業(yè)內(nèi)作為倉庫構(gòu)建核心的元數(shù)據(jù)（業(yè)務和技術(shù)屬性以及對象描述）。另外，他們在區(qū)分集合程度時需要整合和創(chuàng)建同類全局主數(shù)據(jù)以及大量的交易數(shù)據(jù)。</p><p>　　分

4、析師現(xiàn)在詢問的問題要比二十年前的問題復雜得多。這是因為他們知道有數(shù)據(jù)可以解答這些問題。</p><p>　　鑒于上述問題，信息系統(tǒng)需要滿足下列由決策者規(guī)定的要求：</p><p>　　? 直接單點訪問所有相關信息，而不考慮信息的來源</p><p>　　? 涵蓋所有業(yè)務流程：跨系統(tǒng)和跨流程分析變得日益重要</p><p>　　? 高質(zhì)量信息，

5、這不僅指數(shù)據(jù)內(nèi)容，還包括靈活評估數(shù)據(jù)的能力</p><p>　　? 高質(zhì)量的決策支持：BI 系統(tǒng)必須支持運營和戰(zhàn)略管理的需求；只有這樣才能充分支持決策</p><p>　　? 實施時間短、所需資源少：為快速進行實施，數(shù)據(jù)倉庫必須啟用對相關數(shù)據(jù)的簡單而快速的訪問，避免為準備不同數(shù)據(jù)而耗費大量的勞動力</p><p>　　在不同系統(tǒng)布局中，提取和準備來自于 mySAP

6、商務套件應用程序和其他提供商的源系統(tǒng)中的整合交易數(shù)據(jù)和主數(shù)據(jù)是一個特別的挑戰(zhàn)。高質(zhì)量業(yè)務信息需求的日益增長意味著除集成數(shù)據(jù)收集流程外，還需要詳細的數(shù)據(jù)分析和多媒體演示選項。對合并所有這些功能的商務智能解決方案的需求是巨大的。最近，在履行分析角色和運營報表角色時已需要訪問商務智能系統(tǒng)和基本的數(shù)據(jù)倉庫組件，從而便于滿足對準實時數(shù)據(jù)收集的需求。</p><p>　　面向事務的聯(lián)機事務處理（OLTP） 和面向分析的聯(lián)機分

7、析處理（OLAP） 環(huán)境必須被視為單個實體。業(yè)務流程數(shù)據(jù)會產(chǎn)生大量無法輕易用于目標分析的信息。因此，首先清除源數(shù)據(jù)，然后從技術(shù)和語義上準備這些數(shù)據(jù)（均勻化）。從此數(shù)據(jù)的分析中獲取知識。這有助于企業(yè)定義其業(yè)務策略和支持從中派生的業(yè)務流程。</p><p>　　與 OLTP 連接的商務智能特定示例出現(xiàn)在以下兩種業(yè)務情景中：一種針對應付帳，另一種針對銷售和營銷。這兩種業(yè)務情景均利用復雜的數(shù)據(jù)挖掘算法來自動操作和從統(tǒng)計上

8、量化分析結(jié)果。除逐步細化分析工具外，正確操作的數(shù)據(jù)挖掘（屬于 SAP BI 產(chǎn)品）還會增加更多競爭優(yōu)勢。</p><p>　　注意: BW380 包含 SAP 強力推出的數(shù)據(jù)挖掘工具集，而 CR900則包含 SAP BI 和 mySAP CRM 之間的極緊密接口。這些包括通過分析流程設計器和許多其他工具和接口將 CRM 系統(tǒng)的可行動知識轉(zhuǎn)換為自動化。</p><p>　　商業(yè)智能 和數(shù)據(jù)倉

9、儲：定義和好處</p><p>　　由于數(shù)據(jù)處理技術(shù)的不斷創(chuàng)新，越來越多的信息以更詳盡的格式來存儲。因此，需要在減少數(shù)據(jù)的同時對其進行結(jié)構(gòu)化，這樣數(shù)據(jù)分析才變得有意義。根據(jù)收集的原始數(shù)據(jù)創(chuàng)建“商業(yè)智能”所必需的分析需要各種各樣的工具集。</p><p>　　若要設置該階段，首先讓我們來定義一般意義上的商業(yè)之恩給你。在谷歌 中搜索商業(yè)智能，http://whatis.techtarget.c

10、om/ 網(wǎng)站上的《1996 年9 月Gartner Group報表》中解釋了這一術(shù)語，具體定義如下：</p><p>　　“業(yè)務智能(BI) 是指廣義范圍上，用于收集、存儲、分析數(shù)據(jù)，并提供對數(shù)據(jù)的訪問，以便幫助企業(yè)用戶更好地制定業(yè)務決策的應用程序和技術(shù)。BI 應用程序包括決策支持系統(tǒng)的活動、查詢和報表、聯(lián)機分析處理(OLAP)、統(tǒng)計分析、預測和數(shù)據(jù)挖掘?！?lt;/p><p>　　對于廣義的

11、數(shù)據(jù)倉庫，我認為我們要歸功一位研究數(shù)據(jù)倉儲技術(shù)的大師“比爾·艾莫”。1990 年，艾莫先生為“數(shù)據(jù)倉庫”提供了如下定義：1990 年，比爾·艾莫 給出了“數(shù)據(jù)倉庫”的定義：“倉庫是以主題為導向，是與時間相關的非變化、集成式數(shù)據(jù)集合，可以為管理層制定決策時提供支持?！?lt;/p><p>　　更有技術(shù)含量的定義可能是：商業(yè)智能工具集的子集，負責對分析所需要的基本數(shù)據(jù)進行建模、結(jié)構(gòu)化、存儲，并執(zhí)行提取

12、、轉(zhuǎn)換和加載(ETL) 。</p><p>　　因此，商業(yè)智能軟件總的來說是使業(yè)務數(shù)據(jù)變得有意義所必需的應用程序集合。數(shù)據(jù)倉庫是此商業(yè)智能工具集的一個組件，是更專業(yè)地負責清除、加載和存儲企業(yè)所需數(shù)據(jù)的工具。盡管我們在下一章才介紹全套BI工具集，但這一章的重點還是放在數(shù)據(jù)倉庫組件上。</p><p>　　數(shù)據(jù)倉庫可以有助于組織數(shù)據(jù)。它會將所有運營數(shù)據(jù)源（它們大多屬于不同系統(tǒng)，詳盡程度有所不同

13、）結(jié)合在一起。倉庫的工作是以實用形式向整個組織提供此數(shù)據(jù)。然后，可以在將來產(chǎn)生需求時使用該數(shù)據(jù)。</p><p><b>　　倉庫具有如下屬性：</b></p><p>　　? 只讀訪問：用戶具有只讀訪問權(quán)限，這意味著主要通過提取、轉(zhuǎn)換和加載(ETL) 流程將數(shù)據(jù)加載到數(shù)據(jù)倉庫中。</p><p>　　? 跨組織焦點：整個組織（生產(chǎn)、銷售和分銷

14、、成本控制）中的數(shù)據(jù)源和可能存在的外部源構(gòu)成系統(tǒng)的基礎。</p><p>　　? 數(shù)據(jù)倉庫數(shù)據(jù)始終會存儲一定時期。</p><p>　　? 數(shù)據(jù)可長期存儲。</p><p>　　? 為高效查詢處理而設計：對技術(shù)環(huán)境和數(shù)據(jù)結(jié)構(gòu)進行優(yōu)化是為了解決業(yè)務問題，而不是為了快速地存儲交易。</p><p>　　另一位研究數(shù)據(jù)倉儲技術(shù)的大師金伯爾將“數(shù)據(jù)倉

15、庫”定義為“交易數(shù)據(jù)的副本，特別為查詢和分析而重組結(jié)構(gòu)?！保〝?shù)據(jù)倉庫工具，1996 年版，第310 頁）。</p><p><b>　　商業(yè)智能系統(tǒng)目標</b></p><p>　　現(xiàn)代商業(yè)智能系統(tǒng)滿足以下要求：</p><p>　　對所有業(yè)務信息進行標準化構(gòu)造和顯示：決策者急需來自生產(chǎn)、采購、銷售和分銷、財務和人力資源部門的可靠信息。他們需要

16、對每個業(yè)務范圍和企業(yè)整體有一個最新的全面了解。這導致了對收集基本數(shù)據(jù)源數(shù)據(jù)這一流程的高需求。在整個組織內(nèi)單獨定義該數(shù)據(jù)，以避免其他源中的不同定義導致錯誤。</p><p>　　通過單點輸入簡單訪問業(yè)務信息：信息必須在可調(diào)用的中心點按同類和一致性組合在一起。因此，現(xiàn)代的數(shù)據(jù)倉庫通常需要一個單獨的數(shù)據(jù)庫。此數(shù)據(jù)庫啟用獨立的應用環(huán)境來提供所需服務。</p><p>　　用于對所有領域進行自我分析

17、的高度發(fā)展的報表體系：就演示而言，有效的分析和富含意義的多媒體可視化技術(shù)十分關鍵。系統(tǒng)必須能夠處理多個用戶組的信息需求。</p><p>　　快速而高效的實施：在實施數(shù)據(jù)倉庫時，有影響力的成本因子是數(shù)據(jù)倉庫與OLTP 系統(tǒng)的集成及不同數(shù)據(jù)的直接加載。除強大的元數(shù)據(jù)管理功能外，此處推出的基于業(yè)務的商業(yè)智能內(nèi)容還擔當著重要角色。</p><p>　　高性能環(huán)境。不同源的數(shù)據(jù)建模：如果不集成不同

18、的源，則無法通過數(shù)據(jù)倉庫執(zhí)行數(shù)據(jù)分析。這通常會在讀取數(shù)據(jù)時浪費大量時間。計劃工具對于允許在性能友好時間內(nèi)以單獨的批作業(yè)加載數(shù)據(jù)是必需的。</p><p>　　減輕OLTP 系統(tǒng)的負載：過去，OLTP 系統(tǒng)由于需要同時存儲和分析數(shù)據(jù)而嚴重超載。現(xiàn)在，單獨的數(shù)據(jù)倉庫服務器允許您在其他地方執(zhí)行數(shù)據(jù)分析。</p><p>　　BI/數(shù)據(jù)倉庫系統(tǒng)和OLTP 系統(tǒng)之間的區(qū)別</p>&l

19、t;p>　　? 詳細級別：OLTP 層存儲詳細級別非常高的數(shù)據(jù)，而數(shù)據(jù)倉庫中的數(shù)據(jù)則為了在訪問時實現(xiàn)高性能而進行了壓縮（集合）。</p><p>　　? 歷史記錄：在OLTP 領域內(nèi)歸檔數(shù)據(jù)意味著其存儲的歷史記錄最少。而數(shù)據(jù)倉庫范圍需要全面的歷史數(shù)據(jù)。</p><p>　　? 可更改性：數(shù)據(jù)的頻繁更改是運營范圍的一大特色，而數(shù)據(jù)倉庫中的數(shù)據(jù)會在特定點后凍結(jié)以進行分析。</p&g

20、t;<p>　　? 集成：與OLTP 環(huán)境不同，對全面和集成的信息的要求非常高。</p><p>　　? 標準化：由于減少了數(shù)據(jù)冗余，運行使用的標準化程度非常高。數(shù)據(jù)加載和較低性能是數(shù)據(jù)倉庫中標準化程度較低的原因。</p><p>　　? 讀取訪問：針對讀取訪問優(yōu)化OLAP 環(huán)境。運營應用程序（和用戶）也需要定期執(zhí)行包括更改、插入和刪除在內(nèi)的其他功能。</p>

21、<p>　　OLTP 系統(tǒng)和數(shù)據(jù)倉庫/BI (OLAP) 系統(tǒng)的需求存在著根本的區(qū)別。因此，從OLTP 系統(tǒng)中技術(shù)性地區(qū)分所有對數(shù)據(jù)倉庫的集合式、與報表相關的需求是最有利的。</p><p>　　注意: 技術(shù)和特定的業(yè)務案例的發(fā)展會混淆OLTP 分析工具和OLAP（BI 工具）之間的界線。例如，BI 具有準實時提取工具和SAP企業(yè)資源管理計劃中心主件(SAP ECC)，它們可以針對小型公司和特殊情況在同

22、等條件下與BI 環(huán)境一起安裝。</p><p>　　SAP 平臺商務智能：最先進的 BI 軟件</p><p>　　作為 SAP 平臺的核心組件，BI 提供數(shù)據(jù)倉儲功能、商務智能平臺和一套商務智能工具，所有這些能確保企業(yè)最大價值地利用他們所收集的信息。BI 中可以集成、轉(zhuǎn)換和整合 來自 SAP 應用程序和所有外部數(shù)據(jù)源的相關業(yè)務信息。BI 提供靈活的報表和分析工具以支持您評估和說明數(shù)據(jù)，并

23、為數(shù)據(jù)分發(fā)提供便利。企業(yè)能根據(jù)此分析制定出完善的決策，并確定以目標為導向的行動。</p><p>　　BI 套件/商務探測器 (BEx)</p><p>　　包含BEx 的BI 套件提供針對超級用戶和最終用戶的靈活的報表和分析工具。您可以使用這些工具進行戰(zhàn)略分析，并用來支持企業(yè)中的決策過程。這些工具包括查詢、報表和分析功能。BEx確保廣泛用戶能使用 SAP 平臺入口、企業(yè)內(nèi)部網(wǎng)/互聯(lián)網(wǎng)（網(wǎng)

24、絡應用程序設計）或移動設備（WAP 或 i 模式啟用的移動電話和個人數(shù)字助理）訪問 BI 信息。許多分析功能都是可用的；逐步細化（重點功能）只不過是一個開始。另外，還支持許多輸出選項，包括格式化的微軟表格、網(wǎng)絡主控室、格式化的網(wǎng)絡輸出（BEx 報表）和 Adobe PDF 文檔。</p><p>　　BI 數(shù)據(jù)庫可分成獨立的業(yè)務信息提供者。在 BEx 查詢設計器中根據(jù)這些信息提供者定義查詢可分析 BI 的數(shù)據(jù)庫。

25、通過選擇合并查詢中的特性和關鍵值或可重用結(jié)構(gòu)，您可以確定用來分析所選信息提供者中數(shù)據(jù)的方式。</p><p>　　基于多維數(shù)據(jù)源（OLAP 報表）的數(shù)據(jù)分析允許您同時分析信息提供者的多個維度（例如時間、地點和產(chǎn)品）。這意味著您可以進行任意次數(shù)的差異分析（計劃/實際比較和經(jīng)營年度比較）。將類似于主表方式顯示的數(shù)據(jù)作為詳細分析的起點，并可用來回答無數(shù)問題。無數(shù)的交互選項，如排序、篩選、互換特性、重新計算值等，允許您在

26、運行時間靈活地在數(shù)據(jù)中進行導航。您可以用圖形（例如條形圖或餅圖）來使數(shù)據(jù)形象化，還可以在地圖上按地理范圍（針對客戶、銷售區(qū)域和國家這樣的特征）評估數(shù)據(jù)。此外，您還可以使用例外報表來確定特殊情況和重要計量臨界值。當符合這些臨界值時，信息廣播會自動將有關這些問題的消息通過電子郵件或短信服務（SMS）發(fā)送到 知識管理資源庫，通過門戶可訪問這些消息。</p><p>　　您可以在 BEx 中分析以下領域中的數(shù)據(jù)：<

27、/p><p>　　? BEx 分析器（基于微軟表格的分析工具，具有類似于主表的功能）</p><p>　　? BEx 分析器（基于網(wǎng)絡的分析工具，具有類似于主表的功能）</p><p>　　? BEx 網(wǎng)絡應用設計器（由客戶定義并由 SAP BI 內(nèi)容提供）</p><p>　　? BEx 報表設計器（高度格式化的網(wǎng)絡輸出）</p>

28、<p>　　微軟表格和網(wǎng)絡區(qū)域都是無縫集成的。也就是說，您可以在網(wǎng)絡瀏覽器中以標準視圖顯示 BEx 分析器中的查詢，或者可以通過單擊顯示以表格格式呈現(xiàn)的網(wǎng)絡頁數(shù)據(jù)。</p><p>　　BEx 網(wǎng)絡應用設計器</p><p>　　BEx網(wǎng)絡應用設計器允許您在網(wǎng)絡應用程序和 BI主控室中對簡單和高度獨立的業(yè)務情景實現(xiàn)復雜的 OLAP 導航。這些方案可以使用客戶定義的界面要素來創(chuàng)建

29、，而這些界面要素采用標準修飾語言和網(wǎng)絡設計 API。網(wǎng)絡應用設計器包含大量基于網(wǎng)絡的交互式 BI業(yè)務情景，您可以使用標準網(wǎng)絡技術(shù)修改這些方案以滿足您的需求。</p><p>　　您可以使用 BEx網(wǎng)絡應用設計器（一款用于創(chuàng)建網(wǎng)絡應用程序的桌面應用程序）來生成包含 BI 特定內(nèi)容（如各種表、圖表或地圖）的 HTML 頁面。您可以將網(wǎng)絡應用程序另存為 URL，并通過英特網(wǎng)、企業(yè)內(nèi)部網(wǎng)或移動設備來訪問它們。您還可以將網(wǎng)

30、絡應用程序另存為iView，并將它們集成到企業(yè)門戶中。</p><p>　　在創(chuàng)建網(wǎng)絡應用程序時，已將作為助手的 Web 應用程序向?qū)Ъ傻骄W(wǎng)絡應用設計器。它采用自動化的逐步程序和簡化的設計流程。</p><p><b>　　企業(yè)報表</b></p><p>　　BI 中可以有幾種方式實現(xiàn)帶有定位控制和顯示格式的企業(yè)報表（格式化報表）。BEx

31、分析器 的功能是允許使用定制的、高度格式化的表格工作簿，而 BEx 報表設計器則對網(wǎng)絡 輸出或文檔轉(zhuǎn)換為 PDF 執(zhí)行同樣操作。萬一這些選項不能滿足您的需求，則第三方工具可以輕松訪問BI 物理數(shù)據(jù)或物理駐留在其他系統(tǒng)的數(shù)據(jù)。</p><p><b>　　信息廣播</b></p><p>　　信息廣播提供了一種在所需時間按所需頻率執(zhí)行分析的工具集（BEx 網(wǎng)絡、BEx

32、分析器、工作簿和查詢），然后將結(jié)果分配給指定收件人。該分配可以通過例外臨界值觸發(fā)，也可以通過基于網(wǎng)絡的 用戶界面（UI） 來計劃。</p><p><b>　　BI 平臺</b></p><p>　　BI 平臺層包含支持復雜分析任務和功能的 BI 服務。它包含分析引擎，該分析引擎處理通過 BEx 分析導航申請的數(shù)據(jù)，并支持允許輸入和操作數(shù)據(jù)的界面（屬于 BI 集成計劃

33、）。最后，諸如分析過程設計器(APD) 和數(shù)據(jù)挖掘之類的特定分析工具向公司分析師提供合并、挖掘、預處理、存儲和分析數(shù)據(jù)的工具，且不需要技術(shù)團隊的支持。</p><p>　　注意: 新的公司管理準則（如美國的薩班斯-奧克斯利法案）不贊成創(chuàng)建非受控數(shù)據(jù)。APD 允許分析師操作數(shù)據(jù)（例如，他們會在 Microsoft Excel 和 Access 已執(zhí)行這一操作）并將其保留在倉庫之中。</p><p

34、><b>　　移動報表</b></p><p>　　您可以使用 BEx移動智能來調(diào)用通過網(wǎng)絡應用設計器創(chuàng)建的 Web 應用程序。您甚至可以在任何遠離辦公室的時候執(zhí)行此操作。支持以下設備：</p><p>　　? 裝有 Windows CE 3.0 和 Pocket Internet Explorer 的個人數(shù)字</p><p><b

35、>　　助理 (PDA)</b></p><p>　　? WAP 啟用的移動電話</p><p>　　? i 模式啟用的移動電話</p><p>　　? 裝有 EPOC32 操作系統(tǒng)的移動設備（例如諾基亞聊天器9210）</p><p>　　SAP 平臺BI：數(shù)據(jù)倉庫層</p><p>　　數(shù)據(jù)倉庫層是

36、本課的主題，其概覽將在下一節(jié)課中介紹。簡而言之，倉庫負責清除、加載、存儲和管理企業(yè)所需數(shù)據(jù)。</p><p>　　您現(xiàn)在已經(jīng)掌握了基礎知識，但還有一個要點應該注意。與其他 BI 解決方案提供商不同，SAP 為您提供了強大的已交付 BI內(nèi)容。借助于 BI 內(nèi)容，SAP 根據(jù)一致的元數(shù)據(jù)交付預配置的基于角色和任務的信息模型與報表業(yè)務情景。BI 內(nèi)容為公司中的選定角色提供他們執(zhí)行其任務所需要的信息。已交付的信息模型涵蓋

37、所有業(yè)務范圍，并集成幾乎所有SAP 應用程序和選定外部應用程序中的內(nèi)容。 在 BI 項目中，確定用戶需求并設計提取程序是兩件最棘手的事情。借助 BI 內(nèi)容，我們通過網(wǎng)絡或 Excel不僅提供這些內(nèi)容，而且還提供數(shù)據(jù)庫模式、查詢和輸出，這能滿足典型項目 60% 到 90% 的需求。</p><p>　　譯文原文出處：SAP.BI-Enterprise Data Warehousing[M]第3頁-第17頁.HP.2

38、008。</p><p>　　Business Trends and Consequences for Information Systems</p><p>　　Until now, the goal behind the implementation of classic data processing systems has primarily been the accelerati

39、on, cost reduction, and automation of processes in individual business areas. Enterprise Resource Planning (ERP) systems and other software tools now do this in most companies. The result is that these ERP systems, CRM s

40、ystems, banking and credit card systems, and Corporate Governance regulations have exponentially increased data volumes needing analysis. Some consider this a negativ</p><p>　　Decision makers in modern, glob

41、ally operating enterprises frequently realize that their survival depends on the effective use of this information. Unfortunately this information is often spread across many systems and sometimes many countries, thus ma

42、king effective use of information extremely difficult. This is precisely the challenge that modern Business Intelligence systems attempt to meet. Extensive solutions are required to cover the entire process, from the ret

43、rieval of source data to its </p><p>　　As a result of the issues described above, information systems need to meet the following requirements made by decision makers:</p><p>　　?Immediate, single

44、-point access to all relevant information, regardless of source</p><p>　　? Coverage of all business processes: cross-system and cross-process analyses are becoming increasingly important</p><p>

45、　　? High quality of information, not only in terms of data content, but also in terms of the ability to flexibly evaluate data</p><p>　　? High-quality decision-making support: The BI system must support the

46、requirements of both operative and strategic management; only then is it possible to support decisions fully</p><p>　　?Short implementation time with less resources: As well being quick to implement, a Data

47、Warehouse must enable simple and quick access to relevant data, avoiding the labor-intensive preparation of heterogeneous data</p><p>　　In heterogeneous system landscapes, a particular challenge lies in the

48、extraction and preparation of consolidated transaction data and master data from mySAP Business Suite applications and source systems from other providers. The increasing demand for high-quality business information mean

49、s that in addition to an integrated data collection process, detailed data analysis and multimedia presentation options are also require d. The demand for Business Intelligence solutions that incorporate all o</p>

50、<p>　　Transaction-orientated OLTP and analysis-orientated OLAP environments must be considered a single entity. The data for the business processes produces a multitude of information that cannot easily be used for

51、 targeted analysis. Therefore, the source data is initially cleansed, then technically and semantically prepared (homogenized). From the analyses of this data comes knowledge. This helps the organization define its busin

52、ess strategy and supports the business processes derived from it. </p><p>　　Specific examples of Business Intelligence interfacing with OLTP appear in the following two scenarios: one for accounts payable an

53、d one for sales and marketing. Both of these scenarios leverage sophisticated Data Mining algorithms to automate and statistically quantify analysis results. In addition to slice and dice analytical tools, Data Mining (a

54、 part of SAP's BI offering) done correctly adds still more competitive advantage.</p><p>　　Note:BW380 covers SAP's robust delivered Data Mining tool set, while CR900 covers the very tight interfaces

55、between SAP BI and mySAP CRM. These include automation in the return of actionable knowledge to the CRM system via the Analysis Process Designer and many other tools and interfaces.</p><p>　　Business Intelli

56、gence and Data Warehousing:Definitions and Benefits</p><p>　　Due to continuous innovation in data processing, more and more information is stored in a more detailed format. As a result, there is a need to bo

57、th reduce and structure this data so it can be analyzed meaningfully. The analysis necessary to create .business intelligence. from the collected raw data requires a varied tool set.</p><p>　　To set the stag

58、e, let’s first define business intelligence generically. In a Google search for business intelligence, http://whatis.techtarget.com/ attributed the term business intelligence to a September, 1996 Gartner Group report:<

59、;/p><p>　　Business intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions.

60、 BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and Data Mining.</p><p>　　For the generic def

61、inition of a Data Warehouse, I think we need to give the credit to one of the gurus of Data Warehousing .Bill Inmon.. In 1990 Mr. Inmon defined a Data Warehouse as follows:</p><p>　　In 1990, Bill Inmon defin

62、ed a DataWarehouse: A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process .</p><p>　　A more technical definiti

63、on might be: the subset of a Business Intelligence tool set responsible for modeling, structuring, storing as well as extraction translation and loading (ETL) of the underlying data needed for analysis.</p><p&

64、gt;　　So in summary, Business Intelligence software is the collection of applications needed to make sense of business data. The Data Warehouse, a component of this Business Intelligence tool set, is the more specific too

65、l responsible for the cleanup, loading, and storage of the data needed by the business. Although we will address the overall BI tool set in the next lesson, this class focuses on the Data Warehouse component.</p>

66、<p>　　A Data Warehouse can help to organize the data. It brings together all operative DataSources (these are mostly heterogeneous and have differing degrees of detail). The job of the warehouse is to provide this d

67、ata in a usable form to the whole organization. The data can then be used for future requirements as the need arises.</p><p>　　A warehouse has the following properties:</p><p>　　? Read-only acce

68、ss: Users have read-only access, meaning that the data is primarily loaded into the Data Warehouse via the extraction, transformation and loading (ETL) process.</p><p>　　? Cross-organizational focus: DataSou

69、rces from the entire organization (production, sales and distribution, controlling), and possibly external sources, make up the basis of the system.</p><p>　　? Data Warehouse data is stored persistently over

70、 a particular time period.</p><p>　　? Data is stored on a long-term basis.</p><p>　　? Designed for efficient query processing: The technical environment and data structures are optimized to answ

71、er business questions . not to quickly store transactions.</p><p>　　R. Kimball, another guru of Data Warehousing, defines a Data Warehouse as .A copy of transaction data, specially restructured for queries a

72、nd analyses.. (The Data Warehouse Toolkit, 1996, page 310).</p><p>　　Business Intelligence Systems Objectives</p><p>　　A modern Business Intelligence system must meet the following requirements:

73、</p><p>　　Standardized structuring and display of all business information: Decision makers urgently need reliable information from the production, purchasing, sales and distribution, finance, and human reso

74、urces departments. They require an up-to-date and comprehensive picture of each individual business area and of the business as a whole. This results in high demand being put on the data collection process from the under

75、lying DataSources. The data is defined uniquely across the entire organization to a</p><p>　　Simple access to business information via a single point of entry: Information must be combined homogeneously and

76、consistently at a central point from which it can be called up. For this reason, modern Data Warehouses usually require a separate database. This database enables a standalone application environment to provide the requi

77、red services.</p><p>　　Highly developed reporting for analysis with self service for all areas: In terms of presentation, efficient analysis and meaningful multimedia visualization techniques are essential.

78、The system must be able to cope with the information needs of varied user groups.</p><p>　　Quick and cost-efficient implementation: When implementing the Data Warehouse, an influential cost factor is its int

79、egration into an OLTP system and the straightforward loading of heterogeneous data. Alongside robust metadata management, delivered business-based Business Intelligence content also has an important role here.</p>

80、<p>　　High performance environment. Data modeling from heterogeneous sources:</p><p>　　Data analyses can not be carried out via Data Warehouse without integrating heterogeneous sources. This is usually

81、 done with time-consuming read processes. Scheduling tools are necessary to allow the data to be loaded in separate batch jobs at performance-friendly times.</p><p>　　Relieving OLTP systems: In the past, OLT

82、P systems were strongly overloaded by having to store data and analyze it at the same time. A separate Data Warehouse server now allows you to carry out data analysis elsewhere.</p><p>　　Differences Between

83、a BI/Data Warehouse System and an OLTP System</p><p>　　? Level of detail: The OLTP layer stores data with a very high level of detail, whereas data in the Data Warehouse is compressed for high-performance ac

84、cess (aggregation).</p><p>　　? History: Archiving data in the OLTP area means it is stored with minimal history. The Data Warehouse area requires comprehensive historical data.</p><p>　　?Changea

85、bility: Frequent data changes are a feature of the operative area, while in the Data Warehouse, the data is frozen after a certain point for analysis.</p><p>　　? Integration: In contrast to the OLTP environm

86、ent, requests for comprehensive, integrated information for analysis is are very high.</p><p>　　? Normalization: Due to the reduction in data redundancy, normalization is very high for operative use. Data st

87、aging and lower performance are the reasons why there is less normalization in the Data Warehouse.</p><p>　　?Read access: An OLAP environment is optimized for read access. Operative applications (and users )

88、 also need to carry out additional functions regularly, including change, insert, and delete.</p><p>　　There are fundamentally different demands on an OLTP system compared with a Data Warehouse/ BI (OLAP) sy

89、stem.</p><p>　　It is therefore most advantageous to technically separate all aggregated reporting-related demands made on the Data Warehouse from the OLTP system.</p><p>　　Note: Developments in

90、technology and specific business cases are blurring the lines between OLTP analysis tools and OLAP (BI tools). BI, for instance, has near-real-time extraction tools, and SAP ERP Central Component (SAP ECC). can be instal

91、led along with the BI environment in the same box for smaller companies and special situations.</p><p>　　SAP NetWeaver Business Intelligence: State-of-the-Art BI Software</p><p>　　As a core comp

92、onent of SAP Net Weaver, BI provides Data Warehousing functionality, a Business Intelligence plat form, and a suite of Business Intelligence tools that enable businesses to attain the maximum value from the information t

93、hey collect. Relevant business information from productive SAP applications and all external Data Sources can be integrated, transformed, and consolidated in BI. BI provides flexible reporting and analysis tools to suppo

94、rt you in evaluating and interpreting data, as</p><p>　　BI Suite/Business Explorer (BEx)</p><p>　　The BI Suite containing the Business Explorer (BEx) provides flexible reporting and analysis too

95、ls targeted at both power users and end users. You can use these tools for strategic analysis and to support the decision-making process in your organization. These tools include query, reporting, and analysis functions.

96、 BEx enables a broad range of users to access BI information using the SAP NetWeaver Portal, intranet/Internet (Web Application Design), or mobile devices (WAP or i-mode-enabled mobile</p><p>　　The BI databa

97、se is divided into self-contained business information providers (InfoProviders). You analyze the database of BI by defining queries against these InfoProviders in the BEx Query Designer. You can determine the way in whi

98、ch the data from your chosen InfoProvider is analyzed by selecting and combining characteristics and key figures or reusable structures in a query.</p><p>　　Data analysis based on multidimensional Data Sourc

99、es (OLAP reporting) allows you to analyze more than one dimension of an InfoProvider (for example, time, place, and product) at the same time. This means that you can make any number of variance analyses (plan/actual com

100、parison and business year comparison). The data, which is displayed in a manner similar to a pivot table, serves as the starting point for a detailed analysis, and can be used to answer a myriad of questions.</p>

101、<p>　　Numerous interaction options ñ such as sorting, filtering, swapping characteristics, recalculating values, and so on ----allow you to flexibly navigate in the data at runtime. You can visualize the data i

102、n graphics (bar or pie charts, for example) and you can also evaluate data geographically (for characteristics such as customer, sales region, and country) on a map. Moreover, you can use exception reporting to determine