IT industry is notorious of being full of hype. It is not new started since 60’s and 70’s.
IBM takes the lead in creating slogans like
• When in doubt buy IBM.
• No one gets sacked for buying IBM
They created the concept of FUD :Fear, Uncertainty, Doubt in prospects / customers mind so that they listen to IBM.
They have been good at it. From IBM and BUNCH (Burroughs, UNIVAC, NCR, Control Data Corporation (CDC), and Honeywell ) IBM is only the mainframe vendor still going strong. Credit is due to them as big blue has reinvented itself. Remember “Elephant can dance”. Even today WATSON in AI and machine learning is a strong contender. Though the unwritten rule of the industry is innvovation will come from small companies as proven by the number of start-ups and investment in start-ups.
IT industry has a advantage that a commoner does not fully understand the depth and breadth of IT. Today even IT department does not always fully understand all aspects.
Breadth of IT, before internet (HTML, 1995) was limited. A major change or new concept was created every 5 or 10 years in early days.
The concept of E-Commerce was created.
The speed of new concepts like Bigdata, machine learning, AI, Web Service, data driven company, social media, API economy, has increased after the advent of smart phones, 3G/4G. The user base and developer community has increased manifold.
Thirdparty brokers in IT industry like Mckinsey, Forrester, Gartner have started taking advantage of the hype. These organizations coin new jargons and try to predict the unpredictable. For example, in 2015 Bigdata was top trend. By 2017 bigdata is out and Machine learning is top trend. It has become quite like fashion industry, isn’t it?
It is a lot easier in IT now, to create hype as no one, including best IT team in the world, can know every thing about IT.
This (large market) has given rise to new business model leveraged by Google, Facebook, Amazon.
The level of confusion is high hence the question.
There is a big requirement of data scientists. True. It is a fact.
But there are limited supply as the Datascientist role did not exist before. It has been created by the industry recently. It is a difficult role to fulfil.
The role is so difficult to define that there are 14 definitions. Please see the link.
Top 2 definitions are copied below to get a flavour.
1. “There’s a joke running around on Twitter that the definition of a data scientist is ‘a data analyst who lives in California,” — Malcolm Chisholm
2. “A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data,” — DJ Patil
There is no benchmark to calibrate a Datascientist. So it is easy for marketeers to sell as the buyer has no clue. Hence the noise in the market.