Data Transfer Services: Advantages

A major benefit of Data Transfer Services is the ability to offload work from a server to a client. A redistribution of work load boosts response time for production systems that run on servers. After the data is downloaded to the client, the client's processor performs all subsequent data access and processing.

Moving a copy of the data to the client adds robustness to your decision support environment. In the case of a network failure that would temporarily eliminate access to the server's data, you can continue working with your client copy of the data.

You can transfer only the data that you need by using WHERE processing or data set options (such as the OBS= option) or both to dynamically subset the data as it is being transferred to the client or the server. WHERE processing reduces network traffic and gives you only the data that is needed at the client or the server.

Data Transfer Services supports the model of a centralized control point, such as a mainframe, which initiates communication to a network of workstations.

This model enables centralized distribution of data and applications. Automated jobs that can run during non-peak hours can distribute data and applications to multiple computers that need the data and the applications for the next day's work. Similarly, jobs can be set up to query a network of workstations for the purpose of gathering data and storing it in a centralized repository.

Data Transfer Services facilitates data backup. Data and applications can be copied from a client that has limited memory resources to a server that has more memory resources. This provides a backup in case of loss on the client.

In a program development environment, programmers can use Data Transfer Services to make efficient use of network resources. In the early phase of program development, the programmer can use client resources for basic programming activities (such as editing, testing, and debugging) that do not demand high-performance computing resources. However, when program development demands a high-performance environment for testing or data access, the programmer might use Data Transfer Services to relocate the application to the environment that provides the needed resources.

The development environments at many computing installations often have a higher number of users who work on one system than on other systems. On the system with the heaviest load, response time, execution queues, and other performance factors are less efficient because so many people are running applications concurrently.

Using Data Transfer Services, you avoid contention for heavily used computer resources by creating and testing SAS programs on a less busy system (the client), and then transferring the fully developed and tested program to the heavily loaded system (the server).

Each time you execute a program at the client for testing purposes, you avoid adding to the load on the server. This convenient method can result in significant savings of server resources.

For example, suppose you are developing a SAS program that will run as a production program on the server. Your program analyzes data from a SAS data set that is located on the server and creates several reports from the analysis information. To run many tests of the program before it is final and to avoid the delays that result from server connections, create and store the SAS program on the client. Test the program by downloading the SAS data set that is being analyzed by the program, or test the program by using data that is stored on the client. After the program is complete and correct, upload the program file to the server.