SAS Data Integration Studio 发表评论(0) 编辑词条

主要功能：
提取，转换和加载（ETL）
SAS企业数据整合服务器可帮助企业提取，转换和加载整个企业的数据，创建一致的，准确的信息。直观，有针对性性和精确的处理流程设计，可以轻松地构建逻辑处理工作流程，快速识别输入和输出数据流，并创建业务规则的元数据，所有这些都使数据库，数据集快速生成数据流。

SAS还提供了无与伦比的技术支持和专业服务，使组织不断的得到来自供应商的专业支持，超越了强大的以包装变革构建独特的例程。

使数据库，数据集市和数据流的快速生成。
允许您创建的ETL过程，可重复使用，方便地进行修改，并处理的嵌入式数据质量。
对现有的IT投资回报提高提供了多平台的可扩展性和互操作性。

特征：
拥有一个强大的，且易于使用的转换的用户界面，支持协作，共同的流程和数据重用。
单个或多个来源的数据采集，转换，清洗和加载来创建数据仓库，数据集市，或者BI和分析数据存储。
元数据捕获和整个数据集成和转换过程的记录，并立即重新使用。
转换可以运行在任何平台的任何数据源。
准备使用的，包括相关性和频率，分布的分析和汇总统计分析转变。
转换生成向导或Java插件设计模板创建可重用和可重复的是跟踪和数据登记的转换。
在转化过程中通过自定义的可调用的出口，消息队列和Web服务，因此他们在许多不同项目和不同的技术环境重用。
转换可以执行交互式并定于批处理运行在规定的时间或基于事件触发执行。
发布信息框架的档案，一个发布渠道，电子邮件或各种消息队列中间件。
轻松刷新，添加和更新装入。
用户可选的方案优化装载技术。
数据库感知负载技术，包括批量加载设施，指数和关键创造，下降，电子表格截断。
能够轻松地设计，创建并加载OLAP多维数据集。

附:英文原文
Extraction, Transformation and Loading (ETL)
SAS Enterprise Data Integration Server enables organizations to extract, transform and load data from across the enterprise to create consistent, accurate information. An intuitive, point-and-click process design desktop makes it easy to build logical process workflows, quickly identify the input and output data flows, and create business rules in metadata, all of which enable the rapid generation of data warehouses, data marts and data streams.

SAS also provides unparalleled technical support and professional services, giving organizations the flexibility to go beyond the robust prepackaged transformations to build unique routines without fear of losing vendor support for custom work.

Enables rapid generation of data warehouses, data marts and data streams.
Lets you create ETL processes that are reusable, easily modified and have embedded data quality processing.
Increases returns on existing IT investments by providing multiple-platform scalability and interoperability.
Features
A powerful, yet easy-to-use transformation user interface that supports collaboration, reuse of processes and common metadata.
Single or multiple-source data acquisition, transformation, cleansing and loading to create data warehouses, data marts, or BI and analytic data stores.
Metadata is captured and documented throughout the data integration and transformation processes and is available for immediate reuse.
Transformations can run on any platform with any data source.
More than 300 predefined table and column-level transformations.
Ready-to-use analytical transformations, including correlations and frequencies, distribution analysis and summary statistics.
Transformation Generator wizard or Java plug-in design templates for creating reusable and repeatable transformations that are tracked and registered in metadata.
Transformation processes are callable through custom exits, message queues and Web services, so they are reusable in many different projects and different technology environments.
Transformations can be executed interactively and scheduled to run in batch at set times or based on events that trigger execution.
Framework for publishing information to archives, a publishing channel, e-mail or various message-queuing middleware.
Easily refresh, append and update during loading.
Optimize loading techniques with user-selectable options.
Database-aware loading techniques, including bulk load facilities, index and key creation, and dropping and truncating of e tables.
Ability to easily design, create and load OLAP cubes.