Data Analytics vs. Data Science: Which Career Is Best For You?

Data Analytics vs. Data Science: Which Career Is Best For You?

The modern job market is filled with hundreds of interesting job profiles. Because of this, it is quite difficult to determine which job role you should opt for and which one would be the most suitable career path for you.

Adding to the fact that many of these job descriptions and profiles look quite similar only make professionals more confused. To help you with this, we will be discussing the key differences between two of the hottest domains in the market right now—Data Analytics and Data Science.

To compare these two trending tech domains, let’s divide this blog into three sections: Qualifications/Pre-requisites, Job Description and Industry Trends.


One of the major differences between a data scientist and a data analyst is the skill-set they have. Furthermore, the foundations of each of these career paths are significantly different.

A data scientist should be thorough with database systems like MySQL, Hive etc. They should also have hands-on experience with a programming language like Java, MapReduce or Python. Mathematical and statistical understanding and derivation is also a crucial part of a data scientist’s job description. Finally, deep statistical insights and machine learning frameworks like Apache Mahout and Clustering need to be learned.

When it comes to a data analyst, the most important concepts to understand before starting your journey down this career path are data warehousing and business intelligence concepts. You would also need a good amount of exposure to SQL and analytics. A data analyst should also have hands-on experience with big data frameworks like Apache Hadoop, Apache Spark, HBase, MapReduce etc. They also must have proven skills in data storage and retrieval, and data architecture. Finally, an experience in ETL tools like Informatica or Talend is also a necessity.

Which one of the above do you think you are closer to?

Job Description

Now that you know what the pre-requisites of each of these careers is, let’s look at what a data scientist and data analyst do every day.

The main aim of a data scientist is to understand data in terms of a business perspective. The management consults with him to make accurate, data-driven, business decisions. Data scientists always come with a solid foundation of programming, modeling, statistics, and math. Other than this, data scientists have great communication and representation skills.

Depending on their skillset, data scientists can be divided into:

  • Data Researcher
  • Data Developers
  • Data Creatives
  • Data Businesspeople

Data analytics is, in some ways a major role in the data science route itself. Their primary aim is to collect and organize data. Further, they are also responsible for obtaining statistical information out of this data.  Their other responsibilities include data modeling and representation of their findings in terms of charts and graphs.

Just like data scientists, data analysts can be divided into:

  • Data Architects
  • Database Administrators
  • Analytics Engineer
  • Operations Engineers

You may have already made up your mind about which role suits you best. But, just to make your decision even more concrete, here’s the third difference.

Industry Trends

A good understanding of the industry trends in very important for anyone looking at new opportunities. Here’s all you need to know about the data science and data analytics domains.

The average salary for a data scientist reported on is $130,457 per year. Comparing this to a data analyst’s salaries, the number comes down to $69,715 per year.

The data science field is also more popular because of the hype has gotten from several leading firms. It has also been dubbed the ‘Sexiest Career of the 21st Century’ on many occasions. This can be clearly observed by looking at the Google Analytics graph below:

Data Science vs Data Analytics: Google Trends

Both data science and data analytics are great technologies and starting a career in either one of them would lead to an amazing professional growth. With all the differences we discussed in mind, we hope you can easily choose which career path among these two is the perfect one for you.

Furthermore, learning the necessary skillsets to get into a data science or data analyst job role is easier than ever. You can simply take up the Masters Programs at Edureka and become an expert in either of these fields.

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