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  • SD从零开始66 数据仓库的概念

    [原创] SD从零开始66 数据仓库的概念

    数据仓库概念:预览Data Warehouse Concepts:Overview

           本单元解释LIS中的数据仓库概念;

           详细的解释了该概念的各个层次-介绍了后勤数据仓库的各个信息系统并且将要定义该概念在SAP开放信息仓库中的角色;

    数据仓库概念Data Warehouse Concepts

           最新水平的数据仓库概念使用三层模型,出发点是实施高效,集成的信息系统;

           这三个层次细分了数据流,从运作系统中的数据获取直到顶层的信息显示;

           OLTP系统中集成的,运作的应用形成了信息获取的基础;它们充满了大量的主数据和过程数据;信息系统以简洁的和结构化的形式显示这些信息;

           这通过压缩应用数据以获得更简洁,信息丰富的关键数字并在一个数据仓库的数据库表中独立地管理它来达成;

           然后用这种方式获取的统计数据可以用第三层中可用的各种分析工具进行分析;

           这些工具提供了大量的方法,允许以有效的和令人印象深刻的方式分析和表现统计数据;因此他们对于减少现代管理中用于做决策的时间做出了巨大的贡献;

    SAP系统中的后勤数据仓库The Logistics Data Warehouse in the SAP System

           后勤信息系统是SAP开放信息仓库中的一个模块并且提供销售和分销,采购,生产,仓库管理,工厂维护以及质量管理范围的信息;

           在LIS中,重要的信息存储在单个的数据库中;它们和运作系统并行地维护;这里主要的目标是转换运作系统中的详细数据为带高预知性值(high predictive value)的关键数字(key figures);

           更多的信息系统可用于财务会计,控制和人力资源模块;

    在线事务处理Online Transaction Processing

           来自SAP R/2和SAP R/3,以及非SAP系统的模块,可以在OLTP层次归类为集成的应用模块;

           包含在这些模块中的大量数据使业务流程的详细预览(detailed overview)难以实现;

           R/3后勤信息系统通过特殊的更新模块锚定在R/3 OLTP应用中;LIS更新和数据聚合,构成了整个LIS概念的主要原理的一部分;

           更新程序减少进入到它的统计相关的模块的过程数据,就是说,他们在LIS中每隔一定间隔按对象累积相关的数据;然后使用公式和条件来计算信息丰富的关键数字;

           统计数据可在LIS中同过程数据在应用模块中处理时同时更新;这样保证了LIS信息和运作数据保持一致;同样可能的是,更新异步地发生,这样会减少应用系统的系统负荷;

           你可以连接R/3 LIS模块到外部的OLTP系统;

           这样允许,例如,一个R/3系统的LIS更新程序可以由SAP R/2应用程序提供过程数据,那就是说LIS能够成为一个R/2 OLTP系统的R/3 OLAP应用系统;

    后勤数据仓库Logistics Data Warehouse

           SAP信息仓库中的每个物理表被称为信息结构(information structure);所有的信息结构具有同样的结构;

           从真实业务世界分析的对象在信息结构中描述为特性,它们被用作分类数据的基础;统计信息围绕着特性例如供应商,客户或者物料等更新和聚合组织元素例如采购组,物料组,评估范围,工厂或存储区域也能够用作信息结构中的特性;

           时间基础是另外一个聚合选项;数据不只是为每个特性同时也按每个期间累积;对每个信息结构,你可以选择每天,每周或每月数据聚合;

           后勤关键数字为每个特性组合依照预定义的期间单位更新;关键数字是数量的数字,传达了一个简练但是意义丰富的信息量;可以通过数据的累积为每个特性获取关键数字,例如采购订单数量或者生产订单数量;然而,他们也可以采用简单的计数器的形式,例如“number of deliveries”;

           SAP R/3系统为各个应用领域包含大量的标准信息结构;easy-to-use工具也允许你组合特性和关键数字以满足你的需要,产生的结果是自定义的信息结构,然后可以通过单独的更新程序为自定义的信息结构提供数据;

    SAP商业智能SAP Business Intelligence

           商业智能层次提供了大量的方法用于仓库数据的在线分析;

           标准分析使你能够从多个角度分析数据;他们支持很多统计函数,允许无限导航,以及使统计数据能够用来自OLTP层的运作系统的后台数据进行增强;

           柔性分析能够通过报表工具生成并调整以适合公司的需求;他们提供多种可能的布局,允许你定义自己的公式,并且和标准分析一样的方式支持图形;

           此外,在SAP ABAP产品的帮助下,你能够执行你自己的分析以及处理任何仓库信息都没有任何问题,因为后勤数据仓库中的数据是透明地存储的;

           除了来自运作系统的实际数据,计划数据也可以在后勤信息系统中用不同的版本进行管理;计划数据的创建由专门的工具支持,例如分布式功能(distribution functions),交互式图形技术(interactive graphical techniques),以及被证实的预测方法(proven forecasting methods);你可以比较计划数据和实际数据作为标准分析的一部分;

           后勤数据仓库是开放的并且当然允许你使用非SAP产品例如Excel或者Native SQL执行分析;

    SAP后勤信息系统SAP Logistics Information System

           SAP后勤提供了许多的应用相关的信息系统,带有标准的用户接口和相似的基本功能;后勤信息系统中的所有数据都以相同的方式存储;专门工具和方法强调LIS中典型的数据仓库特征;

           下列信息系统是可用的:

               SIS 销售信息系统;

               PURCHIS 采购信息系统;

               INVCO库存控制;

               WMIS仓库管理信息系统;

               PPIS车间信息系统;

               QMIS质量管理信息系统;

               PMIS工程维护信息系统;

               RIS零售信息系统;

    SAP开放信息仓库SAP Open Information Warehouse

           SAP开放信息仓库是所有SAP信息系统解决方案的通称;要重视的是后勤,会计,人力资源等中的“传统的”信息系统不具有相同的结构;每个应用有它自己的方法-只有EIS特写了许多的跨应用的方法;

           SAP开放信息仓库包含下列信息系统:

               EIS执行信息系统;

               LIS后勤信息系统;

               FIS财务信息系统;

               HIS人力资源信息系统;

               CIS控制信息系统;

           SAP开放信息仓库的每个信息系统都以它自己特定的方式和不同的强度实现了上面提到的数据仓库的基本原理;

    从凭证到分析From Document to Analysis

           当一张凭证被记账时,信息结构中相应特性组合的关键数字被更新;

           如果凭证的特性组合在信息结构中没有数据记录存在,则产生一条新的记录并且输入了特性和关键数字;

           如果特性组合已经存在信息结构中,则数据行中的关键数字相应地增加或减少;

           不同的分析可以使用存储在信息结构中的数据为各种类型的特性组合生成清单;

    访问后勤信息系统Accessing the Logistics Information System

           R/3系统提供了访问后勤信息系统的多种可能性:

               所有的关键数字都在信息库中管理并且可以使用不同类型的搜索程序来查找;如果一个搜索成功了,可以为一个关键数字执行标准分析;

               后勤应用层可使用菜单选项Information System来访问;在这里,一个应用层的主要特性的成组的关键数字(例如,采购金额,频率)列示在标准分析中;

               还可能通过后勤控制来调用后勤信息系统的各个应用领域;在这里,特性和关键数字按照标准分析中的主题分组(例如,物料分析,供应商分析);

               调用相关的后勤信息系统的第四种可能性提供在应用层;例如,可能直接地从采购调用采购信息系统或者从销售调用销售信息系统;

    Business intelligence (BI) is an application used for giving meaning to raw data that an organization has. The raw data is cleansed, stored and applied with business logics to be useful for enterprise users to make better business decisions. This data can be presented in the form of reports and can be displayed in the form of tables, charts etc. which is efficient and easier to analyse and make business decisions.

    During all business activities, companies create data about customers, suppliers and internal activities. Based on these data’s, employees of various departments like HR, Finance, Accounting, Marketing etc. prepare their work plan.

    Business Intelligence spans a varied set of toolset, of which the Data Ware House consolidates and loads the data from the different Source Systems, while reporting tools like Query Designer, Web Application Designer, and Analyzer are majorly used to create reports which display the data consolidated by the Datawarehouse for analysing purpose.

    Business Intelligence is a SAP product which majorly focuses on providing its customers/organizations with a user friendly and very useful form of representing data that could be helpful for analyses purpose and making business decisions.

    In summary, Business Intelligence tools transform raw data into reports which used for decision making and business forecasting.

     

    Why do we need Datawarehouse & BI ?

    Organizations have different kinds of data such as finance, Human resource, customer, supplier data etc., which can be stored on different kinds of storage units such as DBMS, Excel sheets, SAP R/3 systems etc...Even the company's internal data is often distributed across many different systems and is not particularly well formatted.

    A Data Warehouse can help to organize the data. It brings together heterogeneous Data Sources which are mostly and differing in their details. Using BI Tools one can derive meaningful reports

    What makes SAP BI more effective BI tool?

    • Single point of access to all information is possible through BI. The data from various sources can be accessed at the single place(i.e BI).
    • Data collected from various sources are presented in the form of reports which is efficient for analysis of the data at a high level.
    • SAP BI provides easy to use GUI and better formatting
    • Some of the key functionality that makes SAP BI better than rest is its ability to analyze multidimensional data sources in both web and MS office environments, flexible dashboards, mobility and a flexible, scalable BI platform. 
    • SAP BI is known for its awesome query performance, while requiring little administration
    • Mobile BI for end users on the go
    • Easy Integration with other platforms

    SAP BI/ Data Warehouse Vs. OLTP systems:   

    OLTP(Online Transaction Processing):   

     

    These systems have detailed day to day transaction data which keeps changing. For example, R/3 or any other database.

    OLAP(Online Analytical Processing):

    These systems have data for analysis purpose. The input for this system is from OLTP systems. The data from the OLTP systems is made use to prepare the data for analysis purpose.

    Business Intelligence is an OLAP system.

      OLTP Systems (Operative Environment) DWH/OLAP Systems(Informative Environment)
    Target Efficiency through automation of business processes Generating Knowledge

    (Competitive Advantage)
    Priorities High availability, higher data volume Simple to use, flexible access to data
    View of Data Detailed Frequently aggregated
    Age of Data Current Historical
    Database operations Add, Modify, delete, update and read Read
    Typical data structures Relational(flat tables, high normalization Multidimensional Structure
    Integration of data from various modules/applications Minimal Comprehensive
    Dataset 6-18 months 27 years
    Archiving Yes Yes
     
     
     
     

    T-Code

    Description

    T-Code

    Description

    SM66

    Global Work Process Overview

    ST02

    Tune Summary

    ST06

    System monitor

    STAD

    SAP workload

    ST05

    SQL Trace

    SE30

    ABAP Trace

    ST12

    Single transaction analysis(including ST05/ST30)

    RSMO

    BW Load monitor

    DB02

    DB Load overview

    ST04

    DB Performance snapshot

    RSBATCH

    BI Background management

    RSODSO_SETTINGS

    Maintenance of runtime parameter of DSO

    RSRV

    Analysis and repair BI Objects

    ST03

    Workload in system

    RSRT

    Query Monitor

    RSRTRACE

    Configure Trace Tool

    SAP Business Intelligence (BI) means analyzing and reporting of data from different heterogeneous data sources. SAP Business Warehouse (BW)integrates data from different sources, transforms and consolidates the data, does data cleansing, and storing of data as well. It also includes data modeling, administration and staging area.

    The data in SAP BW is managed with the help of a centralized tool known as SAP BI Administration Workbench. The BI platform provides infrastructure and functions which include −

    • OLAP Processor
    • Metadata Repository,
    • Process designer and other functions.

    The Business Explorer (BEx) is a reporting and analysis tool that supports query, analysis and reporting functions in BI. Using BEx, you can analyze historical and current data to different degree of analysis.

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  • 原文地址:https://www.cnblogs.com/jellour/p/7130555.html
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