Each important technology has the potential of creating divides between the specialists from a given field. This aspect is more suggestive in the data-driven fields like BI/Analytics or Data Warehousing. The data professionals (engineers, scientists, analysts, developers) skilled only in the new wave of technologies tend to disregard the role played by the former technologies and their role in the data landscape. The argumentation for such behavior is rooted in the belief that a new technology is better and can solve any problem better than previous technologies did. It’s a kind of mirage professionals and customers can easily fall under.
Being bigger, faster, having new functionality, doesn’t make
a tool the best choice by default. The choice must be rooted in the problem to be
solved and the set of requirements it comes with. Just because a vibratory rammer
is a new technology, is faster and has more power in applying pressure, this doesn’t
mean that it will replace a hammer. Where a certain type of power is needed the
vibratory rammer might be the best tool, while for situations in which a minimum
of power and probably more precision is needed, like driving in a nail, then an
adequately sized hammer will prove to be a better choice.
A technology is to be used in certain (business/technological)
contexts, and even if contexts often overlap, the further details (aka requirements)
should lead to the proper use of tools. It’s in a professional’s duties to be able
to differentiate between contexts, requirements and the capabilities of the tools
appropriate for each context. In this resides partially a professional’s mastery
over its field of work and of providing adequate solutions for customers’ needs.
Especially in IT, it’s not enough to master the new tools but also have an understanding
about preceding tools, usage contexts, capabilities and challenges.
From an historical perspective each tool appeared to fill a demand,
and even if maybe it didn’t manage to fill it adequately, the experience obtained
can prove to be valuable in one way or another. Otherwise, one risks reinventing
the wheel, or more dangerously, repeating the failures of the past. Each new technology
seems to provide a deja-vu from this perspective.
Moreover, a new technology provides new opportunities and requires
maybe to change our way of thinking in respect to how the technology is used and
the processes or techniques associated with it. Knowledge of the past technologies
help identifying such opportunities easier. How a tool is used is also a matter
of skills, while its appropriate use and adoption implies an inherent learning curve.
Having previous experience with similar tools tends to reduce the learning curve
considerably, though hands-on learning is still necessary, and appropriate learning
materials or tutoring is upon case needed for a smoother transition.
In what concerns the implementation of mature technologies, most
of the challenges were seldom the technologies themselves but of non-technical nature,
ranging from the poor understanding/knowledge about the tools, their role and the
implications they have for an organization, to an organization’s maturity in leading
projects. Even the most-advanced technology can fail in the hands of non-experts.
Experience can’t be judged based only on the years spent in the field or the number
of projects one worked on, but on the understanding acquired about implementation
and usage’s challenges. These latter aspects seem to be widely ignored, even if
it can make the difference between success and failure in a technology’s implementation.
Ultimately, each technology is appropriate in certain contexts
and a new technology doesn’t necessarily make another obsolete, at least not
until the old contexts become obsolete.
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