SAS Data Integration Studio: Fast Track

Information about SAS Data Integration Business Intelligence solutions are generally made up of three core components: 1. Data Integration 2. Reporting 3. Analytics SAS Data Integration Studio: It is a visual design tool for building processes, i.e. implementing processes and managing processes.

What is SAS Data Integration Studio?

The main changes of SAS Data integration studio are as follows.

A shared metadata surrounding afford constant facts definition throughout all facts resources.

SAS software enables you to hook up with, collect, save, and write facts again to a variety of statistics shops, streams, programs, and structures on a spread of sys tems and in many different environments. As an instance, you may control information in organization resource planning (ERP) machine, relational database management systems (RDBMS), flat files, legacy structures, message queues, and XML Information cleaning and enrichment. Incorporated SAS statistics satisfactory software enables you to profile, cleanse, increase, and monitor information to create regular, reliable statistics.

SAS records Integration Studio affords some of variations and features which can improve the excellent of your statistics.

Extraction, transformation, and loading. SAS statistics Integration Studio permits you to extract, remodel, and load statistics from throughout the employer to create constant, a ccurate statistics. It provides a point-and-click interface that allows designers to build system flows, quickly perceive inputs and outputs, and create commercial enterprise guidelines in metadata, all of which allow the rapid era of facts warehouses, information marts, and facts streams.

Grasp statistics control. SAS records Integration Studio allows you to create a unified view of employer statistics from multiple resources. Semantic facts descriptions of input and output information assets uniquely pick out every example of a business detail (consisting of client, product, and account) and standardize the master information version to offer a single supply of reality. Differences and embedded information first-rate approaches ensure that grasp data is correct. http://aspireit.net/ SAS Authorized Training Partner

Advantages of SAS Data Integration    

SAS data integration reduces development time by enabling the rapid generation of data warehouses, data marts, and data streams.

It controls the expenses of information integration by means of supporting collaboration, code reuse, and not unusual metadata.

It increases returns on present IT investments by using providing multi-platform scalability and interoperability.

It creates technique flows which are reusable, without difficulty modified, and feature embedded facts first-class processing. The flows are self-documenting and assist statistics lineage evaluation.

Main Advantage are Import Existing Code.  Ability to push the processing to the database

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 Performance Statistics    

Start Time, End Time, Duration CPU Time CPU Time, Current Memory System Memory Number of threads.

 Can run jobs on a grid Some Disadvantages of SAS Data Integration Not Many…..  Installation is more complex.  There is a learning curve. Training is required.  Meta Data administrator required.

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Work of SAS Data Integration i.e. Administrative Task 

Set up a folder structure for your site in the Folders tree.

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Promote metadata (additional information and metadata export and import).

Start, stop, and check the status of servers.

Monitor the system and set up system logs.

Back up and restore your system.

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Optimize the performance of the SAS Metadata Server.

Manage SAS metadata repositories.

Set up security.

Set up data servers and libraries for common data sources.

Set up SAS Application Servers.

Set up grid computing (so that jobs can execute on a grid).

Set up scheduling for jobs that have been deployed for scheduling.

Set up change management.

Set up servers and libraries for remote data (multi-tier environments).

Set up support for message queue jobs.

Set up support for Web service jobs and other stored process jobs.

Enable the bulk-loading of data into target tables in a DBMS. Set up SAS Data Quality software.

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Set up support for job status handling.

Set up support for FTP and HTTP access to external files.

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Work with SAS OLAP cubes.

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