What makes mainframes relevant today? Why are they still in use more than 50 years after their inception?

Watch the video below and then come back to read about some specific use cases of SAS® technology in use on IBM mainframe computers.

Mainframes have had many uses

Throughout this half-century of technological evolution, SAS customers have used mainframe systems for a wide array of critical tasks.

In fact, hundreds of organizations have used mainframes for analyzing SMF/RMF log files for performance and capacity management and processing mission-critical jobs accessing 100s of terabytes of corporate data. MXG Software (Merrill’s Expanded Guide to CPE) and Broadcom MICS Resource Management are popular resources to check out for a dive deeper into this topic.

Notably, a Scandinavian bank and a large US telecommunications customer use MXG to analyze their mainframe computer resource usage for all their mainframe applications. The software measures performance, utilization and planning to ensure that mainframe capacity accommodates demand. This results in mainframe system optimization and cost containment while satisfying service level agreements (SLAs) for critical processing.  In addition, this information is pivotal in governing user billing and resource utilization management, helping organizations identify the most expensive users, monitoring runaway resource consumption and managing user groups as they approach expense limits early in a processing month, among other things. This analysis provides insight to business leaders, allowing a mainframe cost/benefit balance.

Throughout this half-century of technological evolution, SAS customers have used mainframe systems for a wide array of critical tasks.

Lastly, this information is used to forecast needed computing resources for anticipated workloads, helping leaders develop plans and budgets to sustain and grow their business.

Hundreds more organizations use SAS on mainframe systems to extract, transform, load, analyze and store massive amounts of data on mainframe systems.

More examples of mainframe usage

For example, one of the largest healthcare management and provider organizations in the US continually gathers and processes historical patient data and claims information on its SAS mainframe. SAS is used to manage this massive data farm and source it for analysis and reporting by the company’s many divisions. This data is used in all aspects of healthcare management, claims payment, cost and utilization management, outcome studies, and tailoring healthcare offered plans. As previously mentioned, organizations also manage their mainframe usage and chargebacks with SAS. Other examples are:

  • A US government agency uses SAS on the mainframe for their military ID processing, running applications to monitor eligibility and controlling the granting and tracking of those IDs.
  • A large automobile manufacturer uses SAS on their mainframe to store their sales and manufacturing data in IBM/DB2®. Like the other mainframe customers, they use SAS to manage their data and source it for analytical reporting to their sales and manufacturing divisions.
  • A large European bank uses the SAS Fraud Management solution on IBM z/OS to process real-time credit card transaction approvals by accessing data on a customer information control system (CICS) via shared memory tools between z/OS and CICS. They require a stable, robust, and real-time system to approve, deny or generate alerts at every card transaction swipe.

Mainframes are continuing to prove their worth, even throughout the digital age. Built to process enormous amounts of data, its continued use is a testament to the resilience and evolution of technology.

Keep reading to learn more information on the SAS and IBM partnership.


About Author

Margaret Crevar

Manager, SAS R&D Performance Lab

Margaret Crevar has worked at SAS since May 1982. She has held a variety of positions since then, working in sales, marketing and now research and development. In her current role, Crevar manages the SAS Performance Lab in R&D. This lab has two roles: testing future SAS releases while they're still in development to make sure they're performing as expected; and helping SAS customers who are experiencing performance issues overcome their challenges.

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