10 Best Universities for Big Data Analytics and Data ScienceFriday, August 6, 2021
You might have heard of the term Big Data. It means a large amount of structured or unstructured data collected from different sources such as websites, mobile apps, and other systems.
Since big data is influencing our daily life in many aspects, the demand for big data-related jobs has been higher than ever. When searching “data analyst” on LinkedIn, 57,635 results appear. Besides data analyst, other big data-related jobs including business analyst, data scientist, data engineer, database manager, data architect and etc are also in high demand.
With the hot demand in the working force in big data analytics, more and more universities start to offer awesome programs for students to pursue a career in the big data industry. These programs may have different names such as Business Analytics, Big Data Technologies, Artificial Intelligence, Data Science, and target students with different skills and backgrounds. But generally, they concentrate on similar fields.
I’d like to list the best 10 master’s programs to study big data analytics in the USA and briefly introduce the concentrations and program features. Let’s take a look.
10 Best Universities for Big Data Analytics and Data Science：
- Massachusetts Institute of Technology: Master of Business Analytics
- Carnegie Mellon University: Master of Science in Information Technology: Business Intelligence and Data Analytics
- University of Chicago: Master of Science in Analytics
- University of Texas at Austin: Master of Science in Business Analytics
- Northwestern University: Master of Science in Analytics
- Cornell University: Master of Professional Studies (MPS) in Applied Statistics
- University of Pennsylvania: Master of Science in Engineering in Data Science
- New York University: MS in Data Science
- Purdue University: Master of Science in Business Analytics and Information Management
- Stanford University: M.S. in Statistics: Data Science
Established in 1914, MIT Sloan School of Management ranks #1 in the QS Business Masters Rankings. Concentrating on Systems, analytics and human-centered data science, it is a great choice for high-tech professionals (such as engineers, mathematicians, computer programmers) who want to take their skill to the next level and build a career in data analytics.
Location: Cambridge, Massachusetts
Course duration: 1 year
2. Carnegie Mellon University: Master of Science in Information Technology: Business Intelligence and Data Analytics
The Heinz College at CMU offers a master’s program in IT that allows students to further their study in Business Intelligence and Data Analytics. It is suitable for early-career professionals with around 3 years of working time in the field of IT, leadership experience preferred. As an online course, it allows students to access all the courses and resources as the on-campus learners, without having to leave where they work.
Location: Pittsburgh, Pennsylvania
Course duration: 2 years
The Master of Science in Analytics program is offered by the Graham School of the University of Chicago. This program welcomes students who are determined to pursue a career in analytics, including those who are either in their early- or mid-career. Students will develop the ability to analyze big data and generate business insights.
Location: Chicago, Illinois
Course duration: 1 year (full-time) or up to 4 years (part-time)
This program equips students with skills in statistical analysis, data mining, natural language processing, and machine learning, to help them gain insights from fields including finance, marketing and supply chain management. Students can also benefit from the incredible networking opportunities with alumni who are industry leaders from Walmart, Deloitte consulting, McKinsey.
Location: Austin, Texas
Course Duration: 10 months
This MSIA program features an 8-months practicum project, a 3-month summer internship with leading companies, and a 10-week capstone project. Students will receive adequate industry exposure to gain practical experience throughout this program.
For students who need training in programming, Northwestern provides special sessions on SAS, SPSS, Cognos, Tableau, etc to help them get prepared.
Location: Evanston, Illinois
Course Duration: 15 months (full-time)
The M.P.S. program consists of two-semester courses covering statistical applications, computing, and consulting, electives from the Department of Statistical Science, and a large-scale data-analysis project in the end (instead of a thesis or exam.) Students will be able to master statistical theory and develop proficiency in the use of statistical software upon graduation.
Location: Ithaca, New York
Course Duration: 1-2 years
Penn’s MSE in Data Science prepares students for a data-driven career, such as technology and engineering, science, consulting.
Location: Philadelphia, Pennsylvania
Course Duration: 1.5-2 years
As the earliest university to have an MS in Data Science program, NYU offers several concentrations for students in this program to choose from, including data science, big data, mathematics and data, natural language processing (NLP) and physics.
There is ample opportunity for training in the form of an internship semester and a capstone project, which allows students to get hands-on experience in collecting and processing the data.
Location: New York, New York
Course Duration: 2 years
I graduated from Purdue with a degree in Hospitality and Tourism Management. It was an amazing study experience in a peaceful city.
Purdue Krannert School of Management offers this program that typically starts in June and continues for 3 semesters. It focuses on supply chain analytics, investment analytics or corporate finance analytics. Through the courses, students will learn to use data analysis tools such as SAS, Python, Minitab, and SQL, which are all great skills to put on the resume.
Location: West Lafayette, Indiana
Course Duration: 1 year
The fields of study in this program include statistics, cognitive science, applied math, engineering science, mathematics, which requires students to possess strong mathematical, computational and programming skills. Upon graduation, students can continue to pursue a Ph.D. degree (but not guaranteed.)
Location: Stanford, California
Course Duration: 1 year
If you are determined to continue your study in Big Data Analytics, one of the most important things is to have cleaned and structured big data sources from the beginning. This can be easily achieved by using data extraction tools like Octoparse, which helps get the data from a large number of websites automatically. The website information, no matter if it's in the form of a video, text, link, or picture, can be scraped and saved into structured formats such as Excel, CSV, JSON, etc. You can also export it into your own system via APIs, which allows you to have more flexibility to store or analyze it.