Ready to learn what big data analysts do, how much they make, and how earning your master’s degree online through SDSU Global Campus can open up the doorway to this growing profession?
What is the job role of a big data analyst?
A large data analyst gathers large volumes of data and interprets it to aid organizations in making strategic decisions. Analysts also uncover insights that influence everything from marketing campaigns to product development to public health initiatives and engineering by spotting trends, patterns, and correlations in data.
Put simply, big data analysts translate information into action. They operate behind the scenes to solve real-world challenges by analyzing complex datasets, sometimes employing programming languages, machine learning tools, and advanced statistical models.
Big data analysts are needed in many areas, such as:
- Finance and Insurance
- Health Care and Public Health
- Marketing and E-commerce
- Government and Urban Planning
- Tech and Information Services
- Education and Research
- Engineering and Manufacturing
In the important areas where data is not being collected, and where it must become a top priority, there is a need for professionals who can make sense of it anywhere it is being collected (and it is virtually everywhere).
What is the salary of big data analyst?
Salaries for Big Data Analysts vary based on experience, education, and industry:
- Median Salary: Approximately $90,723 per year in the U.S.
- Entry-Level Salary: Typically ranges from $60,000 to $75,000 annually.
- With a Master’s Degree: Professionals can expect to earn between $65,000 and $103,500 per year, depending on experience.
Entry-level big data analysts with a master’s degree and a few years of work experience can expect to earn $103,500 per year or more, while those in managerial or specialized positions can earn even more.
Data Analyst Job Growth and Demand
The demand for Big Data Analysts is on the rise:
- Projected Growth: Data scientist roles are expected to grow by 36% from 2023 to 2033, much faster than the average for all occupations.
- Annual Job Openings: Approximately 20,800 openings for data scientists are projected each year over the decade.
The increasing reliance on data-driven decision-making across various sectors drives this growth.
Big Data Analyst: How to Become One
To become a big data analyst, you will need to develop a strong base in analytics, programming, and data modeling. A master’s degree, such as San Diego State University’s Master of Science in Big Data Analytics (available online), is a significant step toward achieving this career path.
Here’s what the journey may look like:
- Earn your bachelor’s degree
A background in computer science, statistics, mathematics, or business analytics is common, but not required. - Enroll in SDSU’s online M.S. in Big Data Analytics
In just 16 months, this flexible, 100% online program teaches you how to collect, manage, and analyze massive datasets to drive decisions across various industries. - Gain hands-on experience
Through applied coursework and real-world research opportunities, you’ll work with tools like Python, SQL, machine learning models, and GIS visualization. - Graduate with a career-ready degree
Earn the same respected degree as SDSU’s on-campus students, backed by a university ranked among the top public institutions in the U.S.
Start your journey with SDSU Online
SDSU Global Campus Online Master of Science in Big Data Analytics is designed for working professionals who want to level up their careers without putting life on pause. The transdisciplinary online graduate program combines technology, business, engineering, science, and social science. In just 16 months, you’ll learn how to compile large data sets, analyze them, and use the results to find patterns, correlations, and insights that businesses and organizations frequently use to make informed day-to-day decisions and drive high-level strategies.
Whether you’re coming from business, IT, healthcare, or the social sciences, this program equips you with the skills to thrive in today’s data-driven world.
