Is Data Science dying?

A Reality Check on the Data Science Hype

Rinu Gour
Towards Data Science
3 min readNov 27, 2019

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STARTING ON

The people who have been in the industry for a long time can relate this. Many years ago the industry went crazy for a similar skill known as Business Analytics. Nowadays, the term Data Scientist is exploding on the internet and it is the modern job that seems very promising.

The image shows the intensity of people searching for Data Science terms on Google.

It’s time to turn your Data Science Dream into a reality

Will Data Science be the Hype in 2020?

Yes, of course. Why? Let’s see.

Big Organizations Support

All the big and even small organizations are driving towards data-driven businesses. The data generated nowadays is too huge to handle manually. We need smart automated techniques to analyze and gather insights that will help organizations to improve business.

Competition is a major factor and the one who doesn’t practice Data Science in his business will soon go out-dated.

Huge Job Opportunities

LinkedIn statistics analyzed the data and ranked data scientists first in “The most promising jobs of 2019”. There is a shortage of a lot of skilled Data Scientists and the number of jobs for this profile is rapidly increasing.

Various Job Profiles

Data Science is a vast field and the definition of a Data Scientist slightly varies in different organizations. A Data Scientist can apply in for multiple job profiles like Data Analyst, Machine Learning Engineer, Data Analyst Consultant, Big Data Engineer, etc.

Money Tree

As the demand for Data Scientists is high and the supply is very low therefore organizations are paying good loads of money. An experienced and talented Data Scientist’s salary is off the charts.

Less Competition

Although everyone might be talking about Data Science, the really skilled people are in fewer numbers. That is why the data science job is easily available. Deloitte predicted 1 million data scientist jobs will be in demand.

Time to be a Data Science Hero and Save Lives

The hype will still be there but now let’s talk about the flip side of the story. Do you think Data Scientists are satisfied with their job?

Many Data Scientists are leaving the sexiest job of all time.

Reasons Why People are switching from Data Science careers

Managers Misinterpretation

Non-technical managers don’t really understand the working of data science and they often misinterpret the work. Developers are not given the right questions to answer and with the communication gap, the organization cannot get the most out of their data. Many developers find it challenging to explain the complexity of the problem.

Unsuitable Infrastructure

Some companies hire a data scientist to solve problems without even having a suitable infrastructure to start with. Data science is all dependent on massive data, there is nothing much you can do with badly organized or inefficient data.

Uncertainty

Sometimes you might be doing everything right, but the solution still doesn’t work out. Yes, that could happen and the reason is Statistics!

You have to live with that. A software developer can implement something at it will work according to plan but this is not true in Data science.

Summing it up!!

People are excited about Data science way too much and therefore everyone wants to move towards data science. Of course, there are a lot of benefits and areas where it excels and you can take advantage but one should be knowledgable about the technology and how it works in order to first implement it in the organization flow. This will make things easier for everyone.

Hope you enjoyed reading!!

Here’s the ticket to your Data Science destination

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Towards Data Science
Towards Data Science

Published in Towards Data Science

Your home for data science and AI. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.

Rinu Gour
Rinu Gour

Written by Rinu Gour

Data Science Enthusiast | Research writer | Blogger | Entrepreneur

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