Why Choose Data Science for Your CareerRinu GourBlockedUnblockFollowFollowingApr 20Data Science has become a revolutionary technology that everyone seems to talk about.
Hailed as the ‘sexiest job of the 21st century’, Data Science is a buzzword with very few people knowing about the technology in its true sense.
While many people wish to become Data Scientists, it is essential to weigh the pros and cons of data science and give out a real picture.
In this article, we will discuss these points in detail and provide you with the necessary insights about Data Science.
Pros and Cons of Data ScienceIntroduction to Data ScienceData Science is the study of data.
It is about extracting, analyzing, visualizing, managing and storing data to create insights.
These insights help the companies to make powerful data-driven decisions.
Data Science requires the usage of both unstructured and structured data.
It is a multidisciplinary field that has its roots in statistics, math and computer science.
It is one of the most highly sought after jobs due to the abundance of data science position and a lucrative pay-scale.
So, this was brief to data science, now let’s explore the pros and cons of data science.
Pros and Cons of Data ScienceThe field of Data Science is massive and has its own fair share of advantages and limitations.
So, here we will measure the pros and cons of Data Science.
This article will help you to assess yourself and take the right course in the field of Data Science.
a.
Advantages of Data ScienceThe various benefits of Data Science are as follows:1.
It’s in DemandData Science is greatly in demand.
Prospective job seekers have numerous opportunities.
It is the fastest growing job on Linkedin and is predicted to create 11.
5 million jobs by 2026.
This makes Data Science a highly employable job sector.
2.
Abundance of PositionsThere are very few people who have the required skill-set to become a complete Data Scientist.
This makes Data Science less saturated as compared with other IT sectors.
Therefore, Data Science is a vastly abundant field and has a lot of opportunities.
The field of Data Science is high in demand but low in supply of Data Scientists.
3.
A Highly Paid CareerData Science is one of the most highly paid jobs.
According to Glassdoor, Data Scientists make an average of $116,100 per year.
This makes Data Science a highly lucrative career option.
4.
Data Science is VersatileThere are numerous applications of Data Science.
It is widely used in health-care, banking, consultancy services, and e-commerce industries.
Data Science is a very versatile field.
Therefore, you will have the opportunity to work in various fields.
5.
Data Science Makes Data BetterCompanies require skilled Data Scientists to process and analyze their data.
They not only analyze the data but also improve its quality.
Therefore, Data Science deals with enriching data and making it better for their company.
6.
Data Scientists are Highly PrestigiousData Scientists allow companies to make smarter business decisions.
Companies rely on Data Scientists and use their expertise to provide better results to their clients.
This gives Data Scientists an important position in the company.
7.
No More Boring TasksData Science has helped various industries to automate redundant tasks.
Companies are using historical data to train machines in order to perform repetitive tasks.
This has simplified the arduous jobs undertaken by humans before.
8.
Data Science Makes Products SmarterData Science involves the usage of Machine Learning which has enabled industries to create better products tailored specifically for customer experiences.
For example, Recommendation Systems used by e-commerce websites provide personalized insights to users based on their historical purchases.
This has enabled computers to understand human-behavior and make data-driven decisions.
9.
Data Science can Save LivesHealthcare sector has been greatly improved because of Data Science.
With the advent of machine learning, it has been made easier to detect early-stage tumors.
Also, many other health-care industries are using Data Science to help their clients.
10.
Data Science Can Make You A Better PersonData Science will not only give you a great career but will also help you in personal growth.
You will be able to have a problem-solving attitude.
Since many Data Science roles bridge IT and Management, you will be able to enjoy the best of both worlds.
b.
Disadvantages of Data ScienceWhile Data Science is a very lucrative career option, there are also various disadvantages to this field.
In order to understand the full picture of Data Science, we must also know the limitations of Data Science.
Some of them are as follows:1.
Data Science is Blurry TermData Science is a very general term and does not have a definite definition.
While it has become a buzzword, it is very hard to write down the exact meaning of a Data Scientist.
A Data Scientist’s specific role depends on the field that the company is specializing in.
While some people have described Data Science to be the fourth paradigm of Science, few critics have called it a mere rebranding of Statistics.
2.
Mastering Data Science is near to impossibleBeing a mixture of many fields, Data Science stems from Statistics, Computer Science and Mathematics.
It is far from possible to master each field and be equivalently expert in all of them.
While many online courses have been trying to fill the skill-gap that the data science industry is facing, it is still not possible to be proficient at it considering the immensity of the field.
A person with a background in Statistics may not be able to master Computer Science on short notice in order to become a proficient Data Scientist.
Therefore, it is an ever-changing, dynamic field that requires the person to keep learning the various avenues of Data Science.
3.
A large Amount of Domain Knowledge RequiredAnother disadvantage of Data Science is its dependency on Domain Knowledge.
A person with a considerable background in Statistics and Computer Science will find it difficult to solve Data Science problem without its background knowledge.
The same holds true for its vice-versa.
For example, A health-care industry working on an analysis of genomic sequences will require a suitable employee with some knowledge of genetics and molecular biology.
This allows the Data Scientists to make calculated decisions in order to assist the company.
However, it becomes difficult for a Data Scientist from a different background to acquire specific domain knowledge.
This also makes it difficult to migrate from one industry to another.
4.
Arbitrary Data May Yield Unexpected ResultsA Data Scientist analyzes the data and makes careful predictions in order to facilitate the decision-making process.
Many times, the data provided is arbitrary and does not yield expected results.
This can also fail due to weak management and poor utilization of resources.
5.
The problem of Data PrivacyFor many industries, data is their fuel.
Data Scientists help companies make data-driven decisions.
However, the data utilized in the process may breach the privacy of customers.
The personal data of clients are visible to the parent company and may at times cause data leaks due to a lapse in security.
The ethical issues regarding preservation of data-privacy and its usage have been a concern for many industries.
SummaryAfter weighing the pros and cons of Data Science we are able to envision the full picture of this field.
While Data Science is a field with many lucrative advantages, it also suffers from its disadvantages.
Being a less-saturated, high paying field that has revolutionized several walks of life, it also has its own backdrops when considering the immensity of the field and its cross-disciplinary nature.
Data Science is an ever-evolving field that will take years to gain proficiency.
In the end, it is up to you to decide whether the pros of Data Science motivate you to take this up as your future career or the cons that help you take a careful decision!Hope you liked our article on the pros and cons of data science.
Share your feedback through comments.
Must read-Many other big companies like Facebook, Amazon, Uber is using it.
Have a look at — Data Science Use CasesHow Data Science is important in Education.