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Debunking myths about BI on the mainframeIs the mainframe still a good environment for business intelligence and analytics?
Claims that the mainframe is a technology near death in the mission-critical world of today’s robust business intelligence (BI) applications are exaggerated. Conventional wisdom says the mainframe – the powerhouse of corporate computing – is simply too costly, too complex and incapable of supporting a comprehensive BI system. Not so. 2. MYTH Predictive analytic applications are not available on the mainframe.
The mainframe minimizes administration costs through extensive self-optimizing capabilities. Proven administration support exists to handle disaster recovery, security, regulatory compliance, performance management and application management. The incremental addition of the BI workload does not substantially add to the existing mainframe administration workload. This significantly reduces the overall cost compared to separately managed, disparate BI environments. A mainframe management simplification strategy also makes it easier to install, configure, administer and maintain. Automation of many of these tasks makes them more straightforward and accelerates administration, again reducing costs. 4. MYTH Mainframe BI solutions are more complex than server-based solutions. One reason for BI complexity is the constantly changing environments – continual upgrades to newer hardware and software versions. Within the mainframe environment, system and software upgrades traditionally are backward compatible. This reduces the cost associated with moving from one release to another, and reduces the complexity of such a move. Using a central server such as the mainframe generates additional savings from reduced network costs, decreased reserve processing power, storage space, and consolidated security and disaster recovery approaches. 5. MYTH The mainframe is too inflexible to handle BI applications and respond quickly to changing requirements. The mainframe provides extremely high availability and proven stability for the most mission-critical applications. Its data integration capabilities are based on the same well-thought-out industry data models created for such verticals as banking and retail. These models give implementers a productivity boost and ensure that most, if not all, necessary attributes to support BI have been included and documented. Having a well-documented and thorough set of models to use for implementation certainly reduces the need to constantly change the ultimate database schema. 6. MYTH Releasing a BI solution into production in a mainframe environment is excessively laborious. Many steps in the release process, such as the testing and certification of the application, are independent of the platform. The hearty mainframe environment supports migration from development to test and production environments quickly. Once these processes are established, their complexity is due to the rigor required to assure a problem-free release of the business intelligence application into production – not because of the platform being used. 7. MYTH It’s old and does not offer modern capabilities. At age 40, the mainframe had to catch up to other server platforms, in terms of Java and open programming. But investments over the last 15 years have enabled the platform to provide an open programming environment that fully supports Java and C++. Furthermore, BI leaders have provided innovative offerings that take advantage of the mainframe platform’s enhancements, ensuring synergy between the software and hardware platform. The mainframe not only offers a nearly infallible operations model; now it also supports modern BI components such as a true real-time or low-latency operational data store, high-speed data management technologies and high performance in mixed workloads.
The mainframe environment for BI includes popular capabilities, such as parallel processing, without requiring any design changes, while simultaneously supporting the ability to support batch and real-time operations. Both are important to evolving BI requirements. The latencies associated with data integration and transfer can also greatly affect an enterprise’s ability to use its BI to make better decisions. Much enterprise data still is hosted by the mainframes. When the raw data resides there, the extract-transform-load process is streamlined because the data does not need to be migrated via the network to another platform. 9. MYTH There are few mainframe experts who know BI. With the open programming model, many BI skills available in server environments are completely transferable to the mainframe environment with minimal additional training. For a company with an existing mainframe, the IT staff already has appropriate programming and maintenance skills necessary to create and support BI applications on the mainframe platform. 10. MYTH The mainframe can’t perform as well as newer solutions. Workflows are managed efficiently by prioritizing queries according to their importance and performance requirements. The ability of a server to handle a workload of mixed queries is a more appropriate and realistic way to evaluate a BI system, but it’s an extremely challenging evaluation to perform. The complexity of the BI workload makes it difficult to run realistic tests. To manage this, the platform requires a workload management function. The mainframe has one of the most robust workload managers available. In addition, the mainframe is much more fault-tolerant than a PC environment, where unplanned outages are common as the PC locks up, gets slower and finally needs to be rebooted. A mainframe reboot is rare, with many applications operating for years without outages. Small wonder that so many vendors declare their machines have “mainframe-like” availability.
Summary
Bio:
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Laurel Buck, a SAS Solutions Architect, is a chief designer of SAS’ simulation laboratory. Read More
This story appears in the Second Quarter 2009 issue of
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