The Downloads section of this article contains a DB2 script that creates the necessary operational (source) table and data warehouse (target) tables.
本文的下载小节包含一个db2脚本，该脚本创建必要的操作型(源)表和数据仓库(目标)表。
This article, the first in a two-part series, illustrated how to build a single data flow that uses an XML-based source table to populate two target data warehouse tables.
本文是一个分两部分的系列的第一篇文章，文中阐述了如何构建一个数据流，该数据流使用一个基于 XML 的源表填充两个目标数据仓库表。
ETL services support the initial and incremental extract, transform, and load of data from one or more source systems to meet the needs of one or more targets, such as a data Warehouse and MDM system.
ETL服务支持从一个或多个源系统提取、转换和装载数据，从而满足一个或多个目标系统(比如数据仓库或MDM系统)的需要。
During this process, operational data is retrieved from a product source as an XML resource, mapped to relational data tables, and normalized in the data warehouse.
在这个过程期间，操作性数据是从一个产品源中获取以作为一个XML资源，映射到关系数据表中，并在数据仓库中得到标准化。
In a well structured BI system, the data warehouse serves as a single source for multiple data marts.
在结构良好的BI系统中，数据仓库充当多个数据集市的一个源。
These attributes were mapped to source system logical data models in order to ensure that attributes were available in the source systems that were to feed the data warehouse.
这些属性被映射到源系统的逻辑数据模型，从而确保能够在源系统中找到提供给数据仓库的属性。
ETL is often used to extract data from the source system, transform data into a compatible format with the target system, and then load into a target system, such as a data warehouse or data mart.
etl常用于从源系统中提取数据，将数据转换为与目标系统相兼容的格式，然后将其装载到目标系统中，例如数据仓库或者数据市场。
Structured source data collected by operational systems—on patients, medical claims, and providers—was fed through extract, transform, load (ETL) processes into the data warehouse.
业务系统收集的结构化源数据 —关于患者、医疗索赔和供应商 —通过提取、转换、加载（ETL）流程输入数据仓库。
With all the necessary relational values extracted from the source XML column, it's time to aggregate the two values needed for one of the target data warehouse tables (the DWADMIN.ACCT table).
从源xml列提取所有需要的关系值之后，便可以为一个目标数据仓库表(DWADMIN .acct表)聚合这两个值。
Traditionally, a BI data warehouse receives data from source systems (usually the operational online transaction processing [OLTP] systems) but never provides data back to them.
传统上，BI数据仓库从源系统(常常是操作性联机事务处理[oltp]系统)接收数据，但是从不向它们返回数据。
To understand how the XML source data in the INFO column of TPOXADMIN. ACCOUNT is mapped to the various columns of the data warehouse tables, see Table 1 and Table 2.
为了理解TPOXADMIN.ACCOUNT的INFO列中的XML源数据如何被映射到数据仓库表的不同列上， 可查看 表1 和表 2。
In a recent TDWI survey, data management professionals were asked "Which types of data and source systems will feed your data warehouse three years from now?"
最近的一次TDWI调查向数据管理专业人员询问，“您认为，在以后三年您的数据仓库中哪种数据和源系统会大量增加？”
Data about what source systems were used to populate the data warehouse, marts, and cubes.
用来填充数据仓库、数据集市和多维数据集的源系统的相关信息。
To understand how the XML source data (in the INFO column of TPOXADMIN.ACCOUNT) is mapped to the various columns of the data warehouse tables, see table 1.
要理解xml源数据(在TPOXADMIN . ACCOUNT的info列中)如何映射到数据仓库表的各个列，请查看表1。
Because they are source-driven, the source data models can be used as AIDS in the process of fully developing the warehouse data repository models.
因为它们是源驱动的，所以源数据模型可以用于协助仓库数据存储库模型的完全开发过程。
The data warehouse is the data environment that can be used as the single integrated source of data for processing information.
数据仓库是一种数据环境，是用于信息处理的单一和综合的数据源。
By using the business database of wide-area water quality auto-monitoring system as data source, we researched IRS and its implementation based on OLAP and data warehouse (DW).
文章以广域水质自动监控系统业务数据库为数据来源，研究了基于OLAP和数据仓库的智能报表系统(IRS)及其实现。
It is the important characteristic of SAS data warehouse technology that the operation of integrated type formed a coherent whole from the data source to the data warehouse.
从数据源到数据仓库一气呵成的集成式的操作，这是SAS数据仓库技术的重要特点。
A data warehouse database modeling solution is often best served by implementing a denormalized duplication of an OLTP source database.
数据仓库的数据库建模方案通过实施一个OLTP源数据库的非规范化的副本来实现。
Then, life cycle cost data warehouse model was designed via features of cost collection object ending up with the establishment of data warehouse system acquiring cost data as data source.
再以成本收集对象的特性设计全生命周期成本数据仓库数据模型，以所获取的成本数据作为数据仓库的数据源，建立了数据仓库。
Data Acquisition is the set of processes that capture, integrate, trans-form, cleanse, reengineer and load source data into the data warehouse and operational data store.
数据获取是获取，集成，转换，清洗，重构和数据加载到数据仓库和ODS系统的一系列的过程。
The data model of RIDS information source, the algorithm of intrusion analysis and the composition of sensor, inspector and data warehouse are introduced.
给出了RIDS信息源数据模型，入侵分析算法，传感器、检测器、数据仓库的构成。
The data model of RIDS information source, the algorithm of intrusion analysis and the composition of sensor, inspector and data warehouse are introduced.
给出了RIDS信息源数据模型，入侵分析算法，传感器、检测器、数据仓库的构成。
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