8 Data Science Specializations: Learn and Compare

As more organizations and businesses begin to understand the value of data science, universities are offering data science tracks in particular specializations as part of their master’s in data science programs. You can prepare for the increasingly complex field of data science by reviewing the tools and methods expected of a professional in your data science specialization area.

The data science specializations offered to students vary by name and scope, depending on the school. However, foundational data science methods of curating, cleaning and analyzing data will generally be a part of any specialization in data science.

What Is a Specialization in Data Science?

Specializations in data science programs may also be known as “concentrations,” “tracks” or “focus areas,” depending on the school. No matter how you refer to it, data science specialties give you the opportunity to learn specialized knowledge that may prepare you to use data to identify knowledge gaps, predict outcomes and identify opportunities for your organization.

These specializations are often available in part-time and full-time programs for both on-campus and online master’s in data science degrees.

Benefits of Specializing in an Area in Data Science

In an online master’s in data science specialization, students acquire specific knowledge and practice skills that may benefit their future careers.

There are a variety of options available for those who have an undergraduate degree in data science, mathematics, computer science or related fields. Choosing a specialization allows you to focus on the aspects of data science that interest you the most. You may also choose to specialize in a field that you expect to have attractive career prospects, such as artificial intelligence and machine learning.

Data Science Specializations

Data science is becoming more integrated with business, science and government. Data science specialities enable you to build the skills you may need to help your organization succeed.

Business Analytics and Intelligence

Learning Outcomes: With a business analytics and intelligence specialization, you will learn how to use data to make business decisions, interpret and relay data information to stakeholders and help solve problems in their organizations.

Specific Skills and Knowledge: These may include:

  • Mathematical process skills
  • Statistical analysis methods
  • Database management
  • Regression modeling
  • Reports production and presentation

Possible Careers: Earning a master’s in business analytics or a master’s in data science with a track in business analytics may prepare you for positions such as:

Prerequisites: Typical prerequisites may include programming coursework, college-level coursework in statistics and calculus.

Data Science With a Computational Track

Learning Outcomes: A focus on the foundations of data science, including data systems, algorithms, data analytics and big data infrastructure, is part of this computational data science specialty.

Specific Skills and Knowledge: These may include:

  • Mechanics of data science tactics and methodologies
  • Technological theory
  • Engineering
  • Statistics
  • Algorithms and data structures
  • Information retrieval

Possible Careers: After completing this master’s in data science with a specialization in computational data science, you may be able to pursue positions in the following fields:

Prerequisites: Examples of prerequisites for a computational data science track include calculus courses and college-level programming courses.

If you are interested in computer science specifically, you may also consider a traditional or online master’s in computer science.

Data Engineering and Warehousing

Learning Outcomes: You’ll learn how to understand the methods and technologies required to manage big data warehouses. You may also learn engineering and problem-solving skills that are based in big data solutions.

Specific Skills and Knowledge: Throughout a data engineering specialization, you may learn about:

Possible Careers: This specialization may prepare you for roles such as:

Prerequisites: Before enrolling in this type of program, you may need to complete a bachelor’s degree in a related field such as computer science, electrical or computer engineering, mathematics, statistics or information systems.

Database Management and Architecture

Learning Outcomes: You’ll typically be taught how to design and manage big data systems, as well as how to curate and process data. These skills may be useful for helping others in your organization access and interpret information.

Specific Skills and Knowledge: Some skills covered in a database management specialization include:

Possible Careers: After finishing this specialization, you may be prepared for these careers:

  • Data engineer
  • Database architect
  • Information modeling engineer
  • Data administrator

Prerequisites: Earning a bachelor’s degree in data science or a related field is a typical prerequisite.

Data Mining and Statistical Analysis

Learning Outcomes: In this data specialization, you’ll combine mathematical and statistical study with in-depth computational and data analytic training.

Specific Skills and Knowledge: Some that may be beneficial in this specialty include:

  • Mathematical and applied statistics
  • Data management
  • Analysis and model-building with large datasets and databases
  • Statistical computing
  • Statistical learning

Possible Careers: A specialization in data mining and statistical analysis may prepare you to be a:

Prerequisites: These may include courses in calculus, algebra, mathematical statistics and programming.

Machine Learning

Learning Outcomes: You’ll be taught methods for using advanced computational algorithms to expand cognitive functions and advance automation. By the end of the program, you’ll see how algorithms and models may be used to solve complex problems.
Specific Skills and Knowledge: Some skills that are covered in a data science machine learning specialization may include:

  • Applied statistics
  • Data mining
  • Information visualization
  • Natural language processing
  • Data and network security
  • Pattern recognition

Possible Careers: Positions that you may be able to pursue include:

Prerequisites: You may be required to have a bachelor’s degree in statistics or applied mathematics for this specialty. Other prerequisites may include having completed college-level coursework in subjects such as statistics, calculus and programming.

Managerial Data Science

Learning Outcomes: In this type of program, you’ll typically be taught methods for managing data science projects. Programs may focus on a mix of technical, interpersonal and project management skills.

Specific Skills and Knowledge: A managerial data science track may cover topics such as:

  • Database systems
  • Programming languages
  • Communication
  • General management
  • Specific business domain knowledge

Possible Careers: This specialization focuses on preparing students for roles such as:

  • Project manager
  • Data science program manager

Prerequisites: Work experience and technical skills related to data science may be prerequisites for pursuing this specialization. Some schools may want you to understand the basics of linear algebra, calculus and programming languages.

FAQs About Data Science Specializations

There are many nuances to the different types of data science specializations. Below, we provide answers to some frequently asked questions that may help make your decision process a little easier.

Which specialization is the best in data science?

Read the data science specializations descriptions above to learn more and help you decide the right path for you. Note that some specialities are highly technical while others will focus more on business and interpersonal skill sets. Your undergraduate education and work experience will also play a role in deciding which data science specialization career path is right for you.

What are the other specialization areas in data science?

Data science is considered an interdisciplinary field, combining computer science, mathematics and business elements. Some schools offer many other options for data science specializations, such as health informatics, geospatial analytics and demography. Many online master’s in data science programs offer flexibility in choosing electives, so you can tailor the curriculum to your interests.

Do I have to declare a specialization in master’s in data science?

You do not have to declare a specialization to pursue a master’s in data science. Many schools offer a general data science track. In some cases, you may develop an interest in a particular speciality after starting your general degree requirements. Elective courses offer the opportunity to build a broad base of knowledge or specialize in a concentration in data science.

Last updated in February 2022