Pros and Cons of Data Science – Know why choose Data Science as a career?

Data Science demand is on the rise and soon it will be an integral part of every organization.

Data Science is the sexiest job of the 21st century, as well as it is one of the highest paying jobs, that has created a lot of buzz in the business world.

Apart from all of its advantages, Data Science is somewhat like a double-edged sword”, that is,  it has some disadvantages also.

Before diving deep into any field you should always have an understanding of both sides of the coin.

In this tutorial, we are going to discuss some of the Pros and Cons of Data Science that will help you to understand things in a better way.

We are living in the age of information and technology where an enormous amount of data is being generated every single second.

This data is generating through various social networking sites, immeasurable numbers of our day-to-day call records, data from various organizations and industries and many other sources as well.

This immense amount of data requires proper management and utilization to understand that what the data is trying to say, for which Data Science always comes to the rescue.

It helps us in analyzing the raw data in different creative ways to derive some meaningful information from it which helps the organization in making data-driven decisions.

This was just a brief to the Data Science now let’s have a look at the various advantages and disadvantages of the field.

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Pros and Cons of Data Science

In TechVidvan’s pros and cons of Data Science tutorial, let’s first discuss what are the advantages of Data Science.

Let’s start:

Advantages of Data Sciencepros of data science

The field of Data Science has a number of advantages.

Following are some of the pros of Data Science:

1. Data Science Can Be Fun

Data Science is a rare field that gives you the opportunities to work with many things together like mathematics, coding, research, analysis, etc.

So, if you love doing all this it can be a really fun job for you that can never be boring.

But the only catch is, being a growing field requires a lot of hard work, learning as well as unlearning because in this field anytime the best solution to a problem will become just a good one.

2. Multiple Job Designations

Being in demand, it has given rise to a large number of career opportunities in its various fields.

Some of them are Data Scientist, Data Analyst, Research Analyst, Business Analyst, Analytics Manager, Big Data Engineer, etc.

3. Ease of Job Hunting

There is an urgent need for Data Scientists in the market, as there is a considerable gap between the demand and the skills for a Data Scientist.

According to a report from LinkedIn, Data Scientist is declared as the most promising job in America in 2019.

In the latest report from LinkedIn, it is one of the fastest-growing jobs published in Dec 2019, the average annual growth rate of the job of a Data Scientist since 2015 is 37% .

The top industries hiring for this role are Information Technology and services, financial services, internet, and computer software.

One of the reports from IBM says that the demand for Data Scientists will soar by 28% by 2020.

4. Customize the Products

Data Science helps organizations to customize their products by understanding the user requirements more efficiently in order to personalize the user experience.

Also, the organizations can improve their sales and increase the revenue because Data Science helps the organizations in estimating that when and where their products sell best.

5. A Highly Paid Career

As Data Scientist continues being the sexiest job, the salaries for this position are also grand.

According to a Dice Salary Survey, the annual average salary of a Data Scientist $106,000 per year.

6. Cost Optimization

The cost to the companies can be optimized very efficiently using Data Science.

It can also help to increase individual productivity and resource utilization.

7. AI is the Future

While talking about the technology, the world is moving with an unbelievable speed.

With the help of Artificial Intelligence, we are trying to make the machine as smart as humans.

Artificial Intelligence makes use of Data Science to figure out the solutions to complex problems by extracting insights from the data.

Some of the advances of AI that might have a great impact

on the future are the automation of transportation (e.g. self-driving cars), Robots playing an important role in many hazardous jobs.

Disadvantages of Data Sciencecons of data science

Everything that comes with a number of benefits also has some drawbacks.

So let’s have a look at some of the disadvantages of Data Science:

1. Data Security

Data is the core component that can increase the productivity and the revenue of industry by making game-changing business decisions.

But the information or the insights obtained from the data can be misused against any organization or a group of people or any committee etc.

2. Complexity

The various techniques and tools used for Data Science can sometimes cost a lot to an organization as some of the tools are very complex and require expert knowledge or training in order to use them.

Also, it is very difficult to select the right tools according to the circumstances because their selection is based on the proper knowledge of the tools as well as their accuracy in analyzing the data and extracting information.

3. Term is Misleading

By the name Data Scientist, everyone will generally think of a person doing things in a scientific manner with the data, but that is not an actual case.

Data Science is actually more of a business than Science.

The term Data Science may also include Data Analysis, Data preparation, Data Management, etc.

The term Data Scientist can be better understood by “Statistical inference”, that is, drawing conclusions from data with the help of statistics.

4. Does Not Allows to Expertise

The field of Data Science uses many different skills to handle the data and to make data-driven decisions for an organization.

A Data Scientist must have knowledge of various skills like programming, machine learning, statistics, business strategies, etc.

But the Data Science might not allow them to go in-depth of any individual field.


Data Science uses the data to make some decisions that can add value to any business in a very effective way.

After going through the pros and cons of Data Science we can now have a better thought of it at a larger picture.

Even after having a lot of advantages and being a very interesting and exciting field it has a few disadvantages also.

Considering both the sides will help you to decide that, “Whether you want to learn Data Science or not?” and will help you in making a very important career decision.

These were the pros and cons of Data Science tutorial.

2 Responses

  1. Ranjith says:

    here is a very good post on data science for giving more information on data science.

    • Priya says:

      Thanks for liking TechVidvan articles on the advantages and limitations of data science. Stay with us for more learning.

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