Data Science Vs. Data Analytics: Understanding the Differences

Person working with computer clusters

Crossing both disciples and industries, the world of using and understanding big data has vast potential for anyone considering a career in the field. As great as that potential is, however, it’s important to understand the multiple approaches to data studies in order to determine which is right for you. 

Defining Our Terms

In the world of data, terms like “data analytics” and “data science” are often used interchangeably. In order to understand which field is right for you, it is important to recognize where these fields differ and what those differences mean in terms of your background and potential for future growth in your career.

While both fields involve looking at and analyzing large data sets, there are two major differences between them:

  • Their scope — Data analytics takes a micro approach to data, digging into the individual details, while data science looks at data on a macro level, trying to understand the bigger picture.
  • Their end goal — Data scientists value their ability to ask the right questions in order to design and construct replicable processes and data models; Data analysts focus on finding concrete, actionable information for a specific data set to identify trends and help their company make strategic business decisions.

How to Determine Which Path Is Right for You

Which best matches your skills and strengths?

If you’re new to the world of big data, you may be under the impression that these careers are reserved for individuals with a strong background in mathematics and computer science. This tends to be the case for students of data science who need advanced coding abilities to design and develop new models. They often have expertise in machine learning, software development and multiple coding languages and require an advanced degree in order to progress in the field.

Data analytics, by contrast, can be an exciting career path for any individual with an interest in the intersection of science, business and engineering and simply must be able to learn the tools needed to make substantive decisions with the number. At Clarkson, we welcome applicants from any academic or professional background in our data analytics programs. We’ll even help you get more comfortable with key skillsets before you start with free online prerequisite courses. 

Which best matches your personal interests?

When trying to determine which path is best for you, it’s important to consider where your personal interests lie and how they intersect with the day-to-day work of each field.

If you love numbers and want the ability to turn big data into smart data, a career in data analytics may be the best professional match to pair with your interests. Data analysts work in the entire lifecycle of data looking for action points to solve real industry problems. This means everything from gathering, managing, storing and transforming data, to analyzing and presenting it in a visually appealing and intuitive way. The information they gather can be used to make strategic decisions within their company, often improving upon the efficiency of the operation.

While data scientists also work within large data sets, the end result is more focused on technical skills, creating tools, systems and frameworks to help address theoretical situations and problems on a larger scale. Data scientists have an extensive background in mathematics, statistics and computational methods enabling them to determine what approach is most appropriate for a given data set and analytical goal, and are focused on asking the right questions to lead them to other avenues of study.

Which best matches your career goals?  

An advanced degree in either data science or data analytics offers excellent career prospects. Recent industry reports show:

  • The demand for these professional skills is quickly outgrowing the supply of such talent.
  • The number of available jobs in these fields continues to increase dramatically. 
  • Both career paths offer competitive earning potential.  

A degree in data science is ideal for those who want to take on senior positions as advanced analytics professionals. They are required to have sophisticated proficiency in a wide range of specialized skills and tools. 

A degree in data analytics will prepare you for positions in virtually any industry. Graduates of our Data Analytics, MS, program build relevant workplace skills that are applicable to many settings including corporations, government, startups and small businesses. 

You may also choose a more focused study of data analytics, narrowing in on a particular industry with specific needs. Clarkson’s MS in Healthcare Data Analytics prepares graduates to address the growing need for data analysis in both hospital and broader public health settings. Students in this program gain practical and marketable skills for visible and successful careers in a variety of health-related settings including:

  • Hospitals
  • Health systems
  • Health insurance companies
  • Medical practices
  • Technology and consulting firms 
  • Pharmaceutical and medical device companies 
  • Healthcare policy companies 

Why Study Data Analytics at Clarkson?

Whether you’re interested in pursuing a career in an entirely different industry or incorporating these skills and methodology into your current role, an advanced degree in data analytics can be transformative. We’re committed to making that transformation attainable by providing flexibility for our students. You can choose to complete your degree in just three semesters as a residential student, or continue working and pursue your degree online. 

Most importantly, we’re committed to the individual success of each student:

“I really think the main strength of our program is that we’re very committed to teaching our students the skills that are relevant in the workplace today…We believe that we are the ones who prepare the students to really be a contributor from day one and really stand out in the crowd of potential applicants in the field of data analytics,” says Boris Jukic, co-director of the MS in Data Analytics program.

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