But there are differences. A trade school focuses exclusively on the technical aspects of data processing. If that's your bent, these schools can do a good job of preparing you. What they fail to offer, of course, is a broader educational atmosphere in which liberal arts and other nontechnical courses can be taken.
Technical trade schools for data processing run the gamut from excellent to deplorable. The good ones have some sort of accreditation. The best are generally associated with the National Association of Trade and Technical Schools (NATTS). This organization is located in Washington, D.C., and it makes sense to contact it before deciding on a school. NATTS offers a variety of booklets and listings that can make your decision easier, to say nothing of making it productive.
One thing to be wary of is the trade school that makes unrealistic promises about job placement. Do your homework just as you would for four-year institutions and community colleges. Most important, begin to develop the attitude that finding a job in data processing, and forging a career in it, is your responsibility, not a placement office's responsibility. While you're learning data processing, be constantly on the lookout for job opportunities. Seek out part-time jobs to supplement your training. Often, such a part-time job turns full-time after graduation.
These are the major avenues of education for someone wanting to enter the data-processing field. There are others - for example, the armed forces provide an extensive and excellent array of training opportunities in all phases of data processing. Like trade schools - and because they are training people to perform tasks - they focus on technology to the exclusion of other academic areas. They also pay their "students" to learn.
Most communities offer some form of data-processing training through adult education courses at local schools. These can provide someone working in another field but wishing to enter data processing with an introduction to the knowledge necessary to make the switch. Even if you have no ambition to become a data processor, but realize, as everyone does these days, the need to have some familiarity with computers, these adult education courses offer an inexpensive and convenient way to pick up that knowledge.
Finally, there is home study. This is the least effective means of preparing yourself for a career in data processing, but again, much depends upon the individual's motivation and desire to succeed. A highly motivated person can get more out of a home-study course than a lazy, uninspired individual taking up expensive chair space at a top university.
Those are the choices. Interestingly enough, the opportunities available in data processing-and the unusual demands it makes-have created an educational situation that runs contrary to patterns associated with other fields, especially in light of some of the studies I've already mentioned.
Technical knowledge is a requisite for entry into data processing, according to my Burke study. But it's the "softer" knowledge - the ability to communicate, to understand the broader business ramifications of data processing, the vision that goes beyond the computer terminal-that determines real success over the long haul. That's why there is an emerging trend for those wanting a career in data processing not to study it in the undergraduate university setting. Generally, the educational flow has been for students attending a two-year community or junior college to move from there into a four-year institution where their credits can be applied toward a degree. With data processing, the opposite approach might make more sense. For one thing, technical knowledge absorbed toward the end of one's educational process has a better chance of sticking.
But there's another reason.
It is dramatically more difficult for an individual to become a well-rounded, educated person. Developing the communications skills (written and verbal English) and an understanding of global business (finance, accounting, political science, negotiating techniques, languages), social issues (psychology, sociology, history, literature), and other disciplines necessary for continued growth in any field is more difficult than learning the technical aspects of data processing.
I can hear the moans now. It sounds as though I'm downplaying technical education for the data processor. Far from it. What I am suggesting is that data processors - like accountants, engineers, scientists, and all other technically based professionals benefit from being able to communicate their technical knowledge and skills.
A number of years ago, Purdue University, a fine institution specializing in engineering, became aware that its graduates, as a whole, did not advance as quickly up the corporate ladder as did graduates from other good engineering schools. Purdue's engineering training was as good as that offered by other institutions. Why, then, was advancement slower?
The answer Purdue came up with was that while its engineering graduates were as technically skilled as their counterparts from other schools, those other institutions had insisted that students take more courses in written and oral communications.
It makes sense. A person can be filled with information, but if that information isn't being effectively communicated to fellow workers and to top management, it remains solely within that individual. It again comes down to viewing technology and knowledge of it as being valuable only to the extent that it contributes to a larger goal. For that to happen, communication must take place.
Doctors are another example of this. Medical schools are slowly but surely integrating courses in the humanities into the medical curriculum. It has to do with social pressure and, because we have become a litigious society, an attempt to lower the risk of malpractice actions against physicians. A recent study indicated that physicians with a pleasant personality and sense of "the human condition" are less likely to be sued for malpractice. Students entering medical school have been chosen, for the most part, because of their academic records involving "hard sciences." Yet when they become physicians they find themselves dealing with human beings, not just scientific theory, and too many of them are unable to bridge the gap.
The same holds true for data processors. Having a firm grasp of a complex system is one thing; conveying data and information to end users in comprehensible, nontechnical language is another.
That is why acquiring a more liberal and well-rounded education before specializing in technical aspects of data processing is an attractive approach to some students with their sights set on a data processing career. It certainly is not for everyone. In fact, it probably is not the approach most men and women should take as they begin preparations for a career in the field. But there is a certain wisdom to it, and as you progress through this book that wisdom will become more apparent, especially for those of you looking to use data processing as a springboard into the world of management.
