In the spirit of Halloween, I call to mind the words of the horror movie icon Freddy Krueger, who asks of his nemesis in Freddy vs. Jason, "Why won't you die?" That's the same question data old-timers ask about the mainframe -- a haunting IT specter, indeed.
We've been hearing about the mainframe's impending demise since the advent of microcomputers in the 1990s. Over the last 20 years, many organizations have downsized their legacy applications and production systems to prepare for the day when these artifacts from an era of lesser technical intelligence disappeared from the computing landscape.
But, just like Jason, the mainframe lives on… and on. In fact, fresh models keep rolling off the assembly line, as the New York Times reported in August about IBM's new zEnterprise EC12. Microcomputers may have facilitated the personalization of information processing, but the mainframe remains a viable option (though a pricey one) for organizations processing huge volumes of information. Mainframes have been a staple in banking and telecommunications, and they're selling well in emerging markets like Asia and Africa, the Times said.
Now big-data has some organizations revisiting mainframe costs and benefits. If big-data benefits are large enough, they may be able to justify the capital investment in a mainframe. And, given this potential, analysts ought to be aware of the mainframe's big-data processing potential.
For those 40 and younger who have not worked in a mainframe environment, that means becoming familiar with this technology. Your big-data analytics may very well run on a mainframe one day. You should learn the operating system syntax and utilities, which are different from those found in Microsoft Windows or Unix systems. You should become familiar with the storage structure and file naming convention. Furthermore, you should become comfortable with workspace allocation and disk-space partitioning. If your organization adopts a mainframe solution to address big-data resources, you'll benefit by understanding the seasoned methods and tools you'll need to do your work.
If you are older than 40, then you may need to brush off your REXX, CICS, and COBOL skills, so you can create new applications using old tools. Or you'll have to learn how to tie analytics into cloud processing and to tailor legacy code to work on mainframes that may also use blade servers. In effect, the old big iron machines have been reengineered to do some new stuff.
Whether you are young or young at heart, the mainframe is a platform that will become or remain a part of your career. It's been said, "A bend in the road is not the end of the road, unless you fail to make the turn." The folks at IBM have made the turns that prevented the mainframe from reaching the end of the road. Similarly, analysts will have to extend their platform awareness.
Like Jason, the mainframe just won't die. Do you think that's an IT trick or a treat?