Data Analytics FAQs

Here are some frequently asked questions about ��vlog��Ƶ University's Master of Science in Data Analytics program, including its new SAS Specialization.

General Program Questions

How long is the program?: Most students in our MS in Data Analytics earn a degree in under 2 years.

How many credits is the program?: 30 credits total.

How many entry points are there?: We have three entry points: fall, spring and summer.

What is the course delivery style?: The master’s in data analytics is 100% online asynchronous. The asynchronous format allows working professionals to learn around their schedule. All lectures and learning activities are designed to be completed by students at their own pace. This allows graduate students in the MSDA program to work, attend family gatherings, and enjoy life without the pressure of needing to attend a physical class.

Is this program truly 100% asynchronous?: Yes, the program is 100% asynchronous.

Do you accept transfer credits?: We accept up to 6 transfer credits. The credits must be at the master’s level. Additional information on the transfer policy can be located by contacting a graduate admissions counselor at gradandadult@alvernia.edu.

What is the career outlook for students graduating with a master's in data analytics?

The future is bright. ��vlog��Ƶ's M.S. in Data Analytics is tailored to prepare individuals for these sought-after careers:

Data Analyst
Data Scientist
Business Intelligence Analyst
Market Research Analyst
Operations Research Analyst
Financial Analyst

According to the U.S. Bureau of Labor Statistics, various roles such as financial analyst, with an average salary of $101,000, market research analyst with an average salary of $71,500, and positions in big data and machine learning, are in high demand. Businesses, both large and small, are actively seeking professionals versed in data analysis and entrepreneurship, capable of leveraging an interdisciplinary approach to unlock the potential of data as a predictive and strategic asset.

What programming languages are taught?: The main programming languages taught in the MS Data Analytics program are Python and R. Additionally, students will gain database experience using SQL.

Do I need a background in computer science or data science?: No, our program is designed for all students to succeed regardless of prior coding experience. We teach all incoming students the basics of programming at the start of the Data Analytics program to ensure both new coders and experts are familiar with standard concepts.

Do I need to know how to code prior to starting?: No, our program is designed for all students to succeed regardless of prior coding experience. We teach all incoming students the basics of programming at the start of the data analytics program to ensure both new coders and experts are familiar with standard concepts. If you have a background in coding, the first course serves as a refresher on syntax. Additionally, programmers and coders come with experience in many different languages. Our Data Analytics course sequence is designed to assist everyone from novice to Pythonistas.

SAS Specialization Questions

What makes the SAS Specialization different from other analytics specializations?

The SAS Specialization focuses on AI‑enabled predictive analytics, machine learning, and data visualization using enterprise‑grade SAS tools widely used in regulated and data‑intensive industries. Unlike tool‑agnostic or theory‑only tracks, this specialization emphasizes applied, transferable analytics skills that support real‑world decision making across modern industries and platforms.

Students gain hands‑on experience with SAS‑based analytics workflows and earn a Credly digital badge that provides verifiable, employer‑recognized evidence of advanced analytics proficiency.

Do I need prior SAS experience to enroll in this specialization?: No prior SAS experience is required. The specialization is designed for graduate students in the MS in Data Analytics and builds SAS expertise progressively. Students leverage their foundational knowledge of analytics and statistics while developing advanced SAS skillsthrough guided, applied coursework.

How does the Credly digital badge benefit my career?: The Credly digital badge provides verified proof of your advanced analytics competencies in AI‑enabled predictive modeling and visualization using SAS. The badge can be shared on LinkedIn, résumés, digital portfolios, and professional profiles, allowing employers to easily understand and verify the specific skills you have demonstrated.

Can this specialization be completed online or asynchronously?: Yes. The SAS Specialization is fully integrated into ��vlog��Ƶ’s online, asynchronous MS in Data Analytics, allowing students to complete coursework without scheduled class times while maintaining academic rigor and hands‑on learning experiences.

How does this specialization align with employer demand?: SAS continues to be widely used in industries such as healthcare, finance, insurance, business analytics, and government, where reliability, governance, and advanced analytics are essential. This specialization aligns directly with employer demand for professionals who can combine AI‑enabled modeling, machine learning, and visualization to support data‑driven decision making in complex environments.

Will the skills I learn be transferable beyond SAS?: Yes. While students gain deep experience using SAS tools, the specialization emphasizes transferable analytics and machine learning concepts that apply across platforms. Graduates are prepared to adapt their skills to other analytics environments while retaining a strong foundation in enterprise‑level analytics practices.

Do all students get the SAS Specialization Badge?: Currently, all MS in Data Analytics students take the required coursework to earn a badge. Awarding of a badge is based on successful completion of DS 507 and DS 613.

����vlog����Ƶ