It’s a no-brainer that the world we’re currently living in is characterized by technology and the internet. Just as the New York Times puts it, it’s Google’s world; we’re just living in it. The more digitized the world becomes, the more data we generate, and the more people we need to work on them.

There are a few professions whose primary focus is data, and you might have your doubts about which one is right for you. Today, we’re going to be comparing two broad fields, data science, and data analytics. So, if you’ve been between these two data fields, rest assured that after this article, you’re going to have your mind made up. Now, let’s take a closer look at each of them and what they entail.

What Is Data Science?

We’ve been over the fact that data is all around us. However, one other thing we should take a look at is data science. The name itself suggests that it’s something that has to do with data. In the simplest words, data science can be described as getting information and insights out of data. Yet, seeing how fast data science is evolving, we shouldn’t get surprised if the definition widens to include other aspects that data science might tackle.


Like any other field, if one wants to join it, they should first fulfill the educational requirements. Data scientists happen to be some of the most educated workers out there. While the level of education you need might depend on the job you’re seeking, a degree in data science, computer science, and information technology might suffice. Also, many data scientists have a background in mathematics, statistics, and hacking.

Not to be repetitive, but it needs to be said, the major you need to graduate in depends all on the specific profession you choose. Some might need numbers more, and some might need the knowledge obtained from computer science or IT degrees.

Skills and tools

Besides education, one should also possess the right skills and tools to succeed in data science. We’re going to be listing those skills down below:

  • Python
  • Java
  • Hadoop
  • Machine learning
  • Data Mining
  • Data Analysis
  • Object-oriented programming

Roles and responsibilities

Certainly, not all the jobs you can get in the data science field have the same exact responsibilities; however, they’re quite similar. This article focuses on the data scientist’s role as one of the most known jobs in this field.

Data scientists work closely with businesses to understand their objectives and create a plan in which the data help achieve that objective. Afterward, they design data modeling processes, developing algorithms and models that make the data extraction easier and more convenient, eventually analyzing the data extracted and reporting them to their employers.

What Is Data Analytics?


Data analytics is a broad field, and as such, it’s an intersection of business, statistics, and information technology. However, for the sake of providing a definition, we could define data analytics as to the field whose focus is the analysis of raw data to make predictions and conclusions.


The level of education you should obtain depends on the job you are applying for. However, an entry-level job in data analytics requires you to obtain a bachelor’s degree in one of the following majors: data analytics and management, engineering, mathematics, finance, economics, information management, and computer science.

Skills and tools

Some of the skills that are required from potential employees in data analytics are:

  • SQL (Structured Query Language)
  • Proficient in Programming Languages
  • Data Management
  • Data Mining
  • Statistical Analysis
  • Data Analysis
  • Data Visualization

Roles and responsibilities

When it comes to roles, the jobs in data analytics don’t necessarily have the same responsibilities. Each position has specific duties. That’s why here we’re focusing on the roles the data analyst (one of the main jobs in data analytics) has. Among the responsibilities of a data analyst are to design and maintain databases and data systems, mine data from different sources, use tools to interpret data, prepare the results of the data, the trends, patterns, and predictions extracted from data, and report them to the employers, and many others.


Data Science and Data Analytics: Jobs

When it comes to job prospects, it’s not like there is a big difference between these two job fields. Knowing that data makes the world go ’round, people working in both these fields are needed not only in technology but in almost every job sector. Data analysts should expect to be hired in fields like marketing, communications, insurance, finance, sales, business consulting, and many others. According to the Bureau of Labour Statistics, data scientists and other similar occupations are on the list of the fastest-growing occupations between 2019-2029.

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Data ScienceData Analytics
  • Data Scientist
  • Machine Learning Engineer
  • Applications Architect
  • Data Architect
  • Machine Learning Scientist
  • Enterprise Architect
  • Infrastructure Architect
  • Business Intelligence (BI) Developer
  • Data Analyst
  • Statistician
  • Data Analyst
  • Business Intelligence Analyst
  • Quantitative Analyst
  • Data Engineer
  • Data Analytics Consultant
  • Operations Analyst
  • Marketing Analyst
  • Project Manager
  • IT Systems Analyst
  • Risk Analyst

Data Science and Data Analytics: Salary

You might expect to find some contrasts between the wages of jobs in data analytics and data science. However, we regret to inform you that this isn’t the case. However, one thing to consider is the type of job you choose and the level that you work in. It’s common sense that those in top-tier levels earn more than those who landed entry-level jobs. According to Glassdoor and Indeed, the salaries in data science can range up to $123,288. Those in data analytics offer similar if not the same wages. According to Indeed, the wages in data analytics range from $62,000 (being the average salary) to $95,0000.


Data Science vs. Data Analytics: Overlaps & Differences

As much as we want to draw a clear distinction between data science and data analytics, this might not happen entirely. One thing we can say is that these two are so similar, and people are not to blame when they confuse them and use their names interchangeably.

Data science is a term that encompasses all the professions that work with data, including here data analytics, data mining, machine learning, and other data disciplines. Data analytics, on the other hand, is more specific and concentrated compared to data science. It focuses on extracting meaningful insights from numerous data sources. At the same time, a typical data scientist has the responsibility to forecast the future based on past patterns extracted from data.

Choosing between a Data Science and Data Analytics Career

Deciding which road you’re going to take in the job market certainly isn’t easy. However, you can make it easier for yourself by focusing first on your interests. What you want to be doing for the rest of your life, work with numbers, or do you have a passion for intertwining business with data and computer science?

Once you make this point clear, you start considering your background, what you’ve studied, and your experience. This step will aid you to understand which field your educational background is most related to, or in case you’ll need to advance your education level to be eligible for a particular you have your eyes on.

Now that we’ve come to the end of the article, there is nothing left to say other than to hope we’ve helped you first grasp the difference between data analytics and data science, and come to the decision which field is the right for you. If you feel like you need additional education for any of these fields, we’re happy to host you at our university on three campuses. The University of the Potomac offers programs in data analytics and management at the bachelor’s level and data analytics at the master’s level. Hope to see you here!