Suppose you build a house. When it's finished it's shiny, new, and clean.
Then you live in it for decades. Stacks of old newspapers litter the floors. Sometimes a bunch of these get thrown out. You only do superficial cleaning, and crud accumulates in all nooks and crannies.
You also want to embrace the new. You enthusiastically follow each fashion trend in furniture, appliances, and so forth. A new chair arrives, but the old one is still in use because grandma gets back pains when she uses the new one. You buy new nice plates and cups, but the old ones are not thrown away, just in case. The new robot vacuum cleaner cleans the living room, but the old one is still in a closet for the cleaning the robot cannot do. Even your replacements of worn out stuff leave leftovers all over the place. Still more crud accumulates in all nooks and crannies.
Sounds like a badly run household, doesn't it? However, it also looks very much how many businesses operate with respect to their IT landscapes. Today, many executives, spurred on by consultants and pundits, are feverishly trying to get on two bandwagons at the same time: the cloud and big data analytics.
Both are more than just fashion, true. There is real substance to their appearance, just as the commercial Internet was not only fashion when it burst upon the scene in the '90s.
But the fact that there is more substance than fashion does not mean that feverish behavior during the dot-com boom did not result in a dot-com bust around the start of the millennium. The boom and bust mainly came from the problem that most initiatives did not have a proper business model. In other words, they didn't have a way to make money, and this was painted over by grand -- but naive -- stories about a new economy.
This time, we're a little bit wiser. We're very much interested in business models to save money by going to the cloud or make it by using big data analytics.
Home free, then? Not quite, because something else is currently making live for these organizations difficult, namely the well known issue of technical debt.
For instance, the cloud is fine for operators like Google, Facebook, Twitter, Netflix, Spotify, Apple, and so forth, who operate huge homogeneous landscapes. And it's fine for startups who are building a new house, so to speak. But most businesses these days trying to get on the bandwagon have medium-sized heterogeneous landscapes reflecting their heterogeneous businesses.
The cloud juggernauts are also the first ones to profit from letting loose simple algorithms on big data -- they're also big data analytics juggernauts. Big data, by the way, is these days also known as "the new oil," a sign of the gold rush fever that currently surrounds it. Always a sign of danger. The medium-sized heterogeneous organizations might have a lot of data (though "a lot" is not very specific, and often is not that much compared to modern day realities) and are now looking at profiting from the new oil.
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