SAS Servers In a Glance : SAS Application Server (SASApp)

Hi Guys,

As we are learning SAS DI Studio, So it is a high time to keep an eye on SAS Servers. We can simply say that we have a list of SAS Servers but here we would put spot light on some important servers only.

SAS Application Server/s : We can easily say that this server is a bucket of all important SAS server. If we would talk with respect to SAS DI Studio, when administrator installs SAS intelligence platform, he define a metadata object which represents SAS server tier . For SMC (SAS Management Console), such type of object is known as SAS Application Server. By default SAS Application Server is named as SASApp.

SASApp is not an actual server while it contains a set of actual servers. In other word, we can say that SASApp is a logical container of actual servers.

 Usually SAS Application Server contains the following servers:

1. SAS Workspace Server: It executes SAS code, it means workspace server reads and writes data. In SAS DI Studio, when we submit any ETL job for execution, SAS DIS generates SAS code to perform execution and submits the SAS code to Workspace Server for processing.

2. Pooled Workspace Server:  This SAS Server automatically use pooling and load balancing.

3. Stored Process Server:  It is also a great time to discuss Stored Processes. Stored processes are SAS programs which are stored and can be executed by client application. These processes are to perform complex work like: to analyze data and creating reports, and then publish / return the results to the client / channel or repository.

So Stored Process Server submits stored processes by SAS for execution.

4. SAS OLAP Server: It creates cubes and processes queries against cubes. OLAP Server processes the data by using multidimensional expressions language (MDX).

5. SAS / CONNECT Server: This server is to move data between client and server machine or we can say that it enables the client to execute code on a remote host. It can also be used for interactive access to remote libraries.

6. SAS Grid Server: This server is to enable platform for LSF to start SAS/CONNECT servers on a SAS compute grid, so that it could execute grid enabled jobs which are created in SAS DI Studio and SAS Enterprise Miner.

7. SAS/SHARE Server:  It enables parallel access of sever libraries from multiple users.

8. SAS Scalable Performance Data (SPD) Server: it enables concurrent processing of large data stores, Data backup and to restore utilities as well as some tuning options.

What Is Data Integration With Consultation Of SAS DI Studio

Hi All,

We are familiar with all the definition of Data warehouse and the four important words which could define the characteristics of data. We can use the data of the data warehouse to perform various things like: Data mining, Business Intelligence and various types of reporting.

We know it, If we want to perform any operation with the data, We have to have fetch the data from the data ware house. It means firstly we need to collect the data from various sources to create in a unified view for a business purpose.

SAS DI or SAS Data Integration is a ETL (Extract, Transform, Loading) tool. It means we can use SAS DI to create the data warehouse or to fetch the data from it to perform various things and again can upload the data to DW.

Four magical key words to define the Data ware house are Subject oriented, Time-Variant, Integrated and Non-volatile. Which are defined in the definition given by Ralph Kimball.

We are not going currently deeper inside the Data warehouse or it's contents.

Here we go for Data Integration and SAS Data Integration Tool :

•  Unified solution to support all project from building data warehouses to migrate to new ERP System and everything in between


•  Process of actively managing all of our organizational data


• Data Integration is the process of consolidating of data from variety of sources to produce unified view


• Can read data from all available and relevant sources


• To clean the data from point of entry to the point of delivery or every touch point in between


• Consolidated view from many operation system to create Data Warehouse and Data mart to support BI and Analytics


• To Support BI, Analytics program and to store business historical data


• Business gets data from many sources and from many vendors, which contain same information (Changes made in one system would get reflect in all system)


•  To load or Migrate the data from any system


• To consolidate multiple databases into one


• To migrate data from legacy system to reduce cost or to upgrade to latest release of critical application


• Provide integrated solution builds from the ground up solution for all need of data integration


• Solutions are time proven to be rock solid and stable


• It requires from simple and one time migration to complex and real time solutions


• ETL from across the enterprise to create consistent and accurate information


• Data quality (Consistent and reliable data)


• Supports impact and change analysis


• Data synchronization


• Metadata Management


• Can read data from any source including : unstructured data, message cube and legacy systems


• SAS DI Studio not only Extract, transform and load the data, it also perform data cleansing and dimension conforming


• Remove mistakes and corrects data, Captures the flow of transitional data and gives a structure to data to be used by BI tools


• Useful in every sector like : Public Sector, Life Science, Manufacturing, Financial …


• SAS DI is a bridge for BI – Directional flow


• Data migration, Data consolidation, Master data Management, Data Synchronization


• Extensibility with custom connection


• User friendly GUI, Metadata capture and less training time


• Allows integration with existing infrastructure


• Secure communication between Server and client

These notes could be useful for SAS Consultation of SAS DI Studio.