Big Data Analytics Master's Degrees: 20

Top Programs These one-year and two-year graduate programs are just what's needed to close the big-data talent gap. Read on to find a school that fits your ambitions and background.

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It's well documented that there's a big data talent gap, but what's being done

about it? What's needed is knowledge and experience. On the first front,

hundreds of colleges and universities worldwide are gearing up business

analytics, machine learning and other programs aimed at analysis of data in a

business context.

Data growth is headed in one direction, so it's clear that the skills gap is a long-

term problem. But many businesses just can't wait the three to five years it might

take today's undergrads to become business-savvy professionals. With that

and InformationWeek's readership in mind, there's a great opportunity for

experienced information management professionals and even data-savvy IT

generalists to fill the talent void. Thus, here's our short list of one- and two-year

business analytics and big-data-oriented masters programs in North America.

All of these programs are geared to candidates who already have undergraduate

degrees, and most favor professionals with three or more years of work

experience. In many cases part-time options are available, so students can

continue to work as they learn more about big data analytics.

This is not a ranking. It's an alphabetical listing of well-known and emerging

masters programs specifically targeting the big data analytics talent gap. We've

included several of the masters programs at elite schools of engineering where

grad-school-supported research programs have sprung up around big data.

Columbia, for example, has its Institute for Data Sciences, Harvard has its

Institute for Applied Computational Science and the University of California,

Berkeley has its AMPLab (which explores the role of algorithms, machines and

people in big data analytics).

Getting into a masters program at an elite school is no guarantee you'll be tapped

for an interesting big data research project working alongside a well-known

professor. Nevertheless, graduates of these schools tend to have their pick of

future employers.

More than half of these schools are offering fairly new masters programs in

business analytics. These tend to be interdisciplinary degrees sponsored by

schools of business. In some cases it's an MBA degree with a specialization in

analytics and information management (see New York University and Rutgers).

In other cases it's a focused, business-meets-analytics program that can be

completed in one year or less (see North Carolina State University, Drexel,

Louisiana State University and Canada's York University). In still other cases,

departments of statistics and operations research have dialed up their applied

learning to create more business- and big-data-oriented programs (see

University of Cincinnati and University of Tennessee).

Those specifically interested in big data analytics as applied to marketing should

investigate Bentley University and DePaul. Insurance and financial services get

special attention at the University of Illinois at Urbana-Champaign, where State

Farm has a research center that offers tuition assistance and internship

opportunities.

Given the number of universities developing business analytics and big-data

related programs, a list of 20 schools can't be comprehensive. Thus, our last

slide offers links to 10 more masters programs for big data analytics, including

new programs at Arizona State, Fordham University and The University of

Maryland.

We encourage schools not listed here to add appropriate masters programs

using the comment tool at the bottom of the page (note: all comments that

include URLs must be reviewed before posting to eliminate spam, so either omit

links or count on a delay). It will take some time to fill the big data talent gap, so

we'll be updating and expanding this career-development compendium as a

service to our readers.

Bentley University, Waltham, Mass.

Degree: Master of Science In Marketing Analytics

School: Graduate School of Business

Description: Offers a grounding in strategic marketing and training in making

marketing decisions based on quantitative analysis. Program enables students to

make informed marketing decisions based on relevant data and to demonstrate

the financial impact of those decisions. You'll be able to analyze large amounts of

information to develop customer profiles, determine target markets and segment

the customer base.

Prerequisites: Undergraduate degree and GMAT or GRE test results. Students

may be required to take up to five foundation courses covering economics,

statistics, accounting, finance and marketing. Students may be waived from

some or all of these foundations if they have completed an equivalent course

within the past five years from an accredited institution and have earned a grade

equivalent to a B or better.

Full-time program: 1 to 1.5 years.

Part-time options: Yes

Distance learning options: No

Carnegie Mellon University, Pittsburgh, Pa.

Degree: Master of Information Systems Management with a concentration in

Business Intelligence and Data Analytics.

School: Heinz College (Public Policy & Information Systems)

Description: Blended business-technology program designed to foster better

planning, management and technical abilities. The concentration in Business

Intelligence and Data Analytics is designed for cross-training in business process

analysis, predictive modeling, GIS mapping, analytical reporting, segmentation

analysis and data visualization. Students gain hands-on experience through

coursework and through applied research experiences at Heinz College's iLab.

You'll work with real-world data sets describing behaviors of people using mobile

devices, social and digital media environments, smart transportation and health

care services.

Prerequisites: Successful students have demonstrated an ability to synthesize

complex quantitative and qualitative concepts. Candidates tend to have a non-

liberal arts undergraduate background that can vary from engineering, to

information systems to physics. All students are required to complete a college-

level, object-oriented programming course prior to beginning classes at Heinz

College.

Full-time programs: 1 year for Master of Information Systems Management. 16

months for students pursuing concentration in Business Intelligence and Data

Analytics.

Part-time options: No

Columbia University, New York, N.Y.

Degree: Masters of Science in Computer Science, concentration in Machine

Learning

School: The Fu Foundation School of Engineering and Applied Science

Description: The Computer Science department offers masters concentrations

in eight disciplines: Computational Biology, Computer Security, Foundations of

Computer Science, Machine Learning, Natural Language Processing, Network

Systems, Software Systems and Vision and Graphics. The Machine Learning

concentration covers techniques and applications in areas such as

bioinformatics, fraud detection, intelligent systems, perception, finance, and

information retrieval.

The School of Engineering is the home of the Institute for Data Sciences and

Engineering, which will engage 300 masters students and 150 doctoral students

in its education and research programs focusing on problems relating to big data.

Prerequisites: Undergraduate degree in computer science or a related discipline

with a minimum GPA of 3.3 (3.5 or higher is typical). Those with undergraduate

degree in a different field must complete at least four computer science courses

covering foundations of the field and basic programming, and two mathematics

courses.

Full-time program: 2 years.

Part-time options: Yes. Up to five years to complete the degree.

Distance learning options: Selected courses.

DePaul University, Chicago, Ill.

Degree: Master of Science in Predictive Analytics

School: College of Computing and Digital Media

Description: Graduates obtain a variety of skills required for a career in

predictive analytics, including the ability to analyze large datasets and to develop

modeling solutions for decision support. Students also gain a good

understanding of the fundamental principles of marketing and customer

relationship management along with communication skills to present results to a

non-technical business audience. Students can pursue concentrations in

computational methods or marketing.

Prerequisites: Bachelor's degree with a minimum 3.0 GPA. Related professional

experience is recommended. Students can take the GAE to test out of

prerequisite course requirements.

Full-time program: 2 years.

Part-time options: Yes. No time limit on earning degree as long as you remain

enrolled.

Distance learning options: Yes. Degree can be completed entirely online.

Drexel University, Philadelphia, Pa.

Degree: Master of Science in Business Analytics

School: LeBow College of Business

Description: Explores quantitative methods, uncovering relationships through

data analysis, and the use of data to solve business problems. Students learn

how to influence decision-making, strategy and operations with fact-based

insights and business performance analysis. Program addresses statistical and

quantitative analysis as well as explanatory and predictive modeling with courses

on statistics, operations research, mathematical modeling and management

information systems.

Prerequisites: Candidates evaluated based on graduate test scores,

undergraduate GPA and work experience. Work experience is preferred but not

mandatory. GMAT is required with scores demonstrating a high-level of

quantitative and analytical ability.

Full-time program: 1 year.

Part-time options: Yes

Distance learning options: No

Harvard University, Cambridge, Mass.

Degree: Masters of Science in Computational Science and Engineering

School: School of Engineering and Applied Sciences

Description: One-year program developed in 2010 by Harvard's Institute For

Applied Computational Science (IACS). Provides mathematical and computing

foundations complemented by independent research projects and elective

courses. Graduates will master mathematical techniques for modeling and

simulation of complex systems; parallel programming and collaborative software

development; and efficient methods for organizing, exploring, visualizing,

processing and analyzing very large data sets.

Prerequisites: Undergraduate degree in the natural sciences, mathematics or

engineering. GRE test required.

Full-time program: 1 year.

Part-time options: Limited

Distance learning options: No

Louisiana State University, Baton Rouge, La.

Degree: Master of Science In Analytics

School: E.J. Ourso College of Business

Description: Designed to meet the demand for professionals who understand

big data and have the analytics skills needed to extract actionable information

from large and complex data sets. Curriculum emphasizes use of advanced data

management tools and applied statistical and operations research techniques to

analyze large, real-world data sets in order to increase return on investment,

improve customer retention, reduce fraud and improve decision making.

Students receive training in SAS, SQL, R and other tools. Student teams work

with companies and government organizations to solve business problems in

areas such as insurance, banking, health care, communications, e-commerce,

law enforcement and marketing.

Prerequisites: Undergraduate degree with 3.0+ GPA. GMAT or GRE test

scores. Chances of acceptance are higher for prospects with a relevant

undergraduate degree in engineering, computer science, management, science,

operations research, production/operations management, economics, statistics,

mathematics or industrial/organizational psychology.

Full-time program: 12 months.

Part-time options: No

Distance learning options: No

Massachusetts Institute of Technology, Cambridge, Mass.

Degree: Master of Business Administration

School: The MIT Sloan School of Management

Description: Curriculum and degree requirements encourage choice and

experimentation. After a shared first-semester "core," students design a

personalized course of study. Students receive either an MBA degree or, with the

completion of a thesis, a Master of Science in Management. Specialized tracks

are offered in Finance, Entrepreneurship & Innovation, Enterprise Management

and Sustainability.

Sloan is the home of the MIT Center for Digital Business, which pursues

research on the digital economy. The center works with well-known MIT

researchers, such as Professors Erik Brynjolfsson, Glen Urban, Andy McAfee

and Michael Cusumano, and draws on MIT Sloan students to drive research

projects.

Prerequisites: Proven academic excellence and achievement as reflected in test

scores, academic records and personal recommendations. Work experience is

not required, but those who have it "generally get more out of the program,"

according to admission guidelines. College graduates from all areas of

concentration are accepted, but applicants may be required to take courses in

microeconomics, calculus or financial accounting before starting MBA studies.

Full-time program: 2 years.

Part-time options: Yes. MIT Executive MBA (20 months part-time).

Distance learning options: No

New York University, New York, N.Y.

Degree: Master of Business Administration, specialization In Business Analytics

School: Stern School of Business

Description: Teaches the use of data and models to support decision making.

Students learn how to model such relationships as the impact of advertising on

sales, how historical data predict stock returns, and how changes in task

characteristics can influence time to completion. Courses cover data mining,

decision models, econometrics, forecasting time series data, risk management,

trading strategies and systems and regression and multivariate data analysis.

The Stern School is the home of The Center for Business Analytics, an inter-

disciplinary research initiative focused on the use of statistical, machine learning,

econometric, optimization and experimental methodologies with massive

datasets.

Prerequisites: Students have undergraduate degrees in a variety of academic

backgrounds, including liberal arts, engineering, social sciences and business.

GMAT score or GRE scores will be considered. Most applicants have between

one and ten years of work experience (average is five) in professions such as

consulting, financial services, entertainment, consumer products, nonprofit and

technology.

Full-time program: 2 years.

Part-time options: Yes. Part-time and Executive MBA programs.

Distance learning options: Selected courses.

North Carolina State University, Raleigh, N.C.

Degree: Master of Science In Analytics

School: Institute for Advanced Analytics

Description: Established in 2007, this 10-month program is designed to give

students a thorough understanding of the tools, methods, applications and

practice of advanced analytics. The goal is to provide an education that is directly

applicable to a career in industry rather than to provide a prelude to a PhD.

Topics include data mining, text mining, forecasting, optimization, databases,

data visualization, data privacy and security, financial analytics, and customer

analytics, as well as communication and teamwork skills. Team projects are

based on analytical problems using real data from sponsoring organizations.

Prerequisites: Past academic studies in mathematics, statistics, engineering,

science, computer programming, business and economics are relevant

prerequisites. About half of applicants have prior graduate education, including

MS, MBA and PhD degrees. Applicants must hold a bachelor's degree and have

a proven track record of strong academic performance. Prospective students

who have not majored (or minored) in mathematics or statistics will need to have

successfully completed prerequisites in these subjects to be admitted.

Full-time program: 10 months.

Part-time options: No

Distance learning options: No

Northwestern University, Evanston, Ill.

Degree: Master of Science in Analytics

School: McCormick School of Engineering and Applied Science

Description: Curriculum explores data science, information technology and

business analytics. Combines mathematical and statistical study with instruction

in advanced computation and data analysis. Students learn to identify patterns

and trends, interpret and gain insight from vast quantities of structured and

unstructured data, and communicate their findings.

Encompasses three areas of data analysis: predictive (forecasting), descriptive

(business intelligence and data mining), and prescriptive (optimization and

simulation). Program is supplemented by an internship placement and industry

supplied projects.

Prerequisites: Bachelor's degrees in engineering, business, computer science,

math and information technology are typical, though no specific type of

undergraduate degree is required. GPA of at least 3.0 is recommended.

Full-time program: 15 months.

Part-time options: Northwestern University's School of Continuing Studies also

offers a part-time Master of Science in Predictive Analytics Onlineprogram.

Distance learning options: Yes. See part-time, online Predictive Analytics

degree above.

Rutgers University, New Brunswick, N.J.

Degree: Master of Business And Science degree in Operations Research and

Business Analytics

School: Graduate School, Professional Science Masters Programs

Description: Program unites the fields of data management, statistics, machine

learning and computation for data-driven decision making. Students learn how to

analyze large datasets and to develop modeling solutions to support decision

making. Curriculum integrates courses in analytics with business to give students

a good understanding of how data analysis drives business decision making.

Prepares students for careers as predictive modelers, data-mining engineers or

analysts in data-driven industries such as marketing, finance, health care and

biotechnology.

Prerequisites: Bachelors degree in any science or engineering field with a GPA

of 3.0+. Students of science lacking a computing background are urged to apply

but may need to take a basic computing course that can count toward the

degree.

Full-time program: 1.5 to 2 years.

Part-time options: Yes

Distance learning options: No

Stanford University, Stanford, Calif.

Degree: Master of Science In Computer Science, Specialization in Information

Management and Analytics

School: School of Engineering, Computer Science Department

Description: Covers the principles of modern database and information

management systems as well as methods for mining massive data sets. Topics

range from system design, architecture and management to applying algorithms,

data-mining and machine-learning techniques to perform analyses over large

data sets. Related topics include distributed systems, networking and security on

the system side as well as text mining, bioinformatics, Web search and social

media applications.

Stanford also offers a four-course graduate certificate in Mining Massive Data

Sets.

Prerequisites: Candidates must have acquired the foundations of computer

science at the level of an undergrad minor at a minimum. At Stanford these

foundations include courses on the mathematical foundations of computing,

programming methodology and abstractions, computer organization and

systems, object-oriented systems design and principles of computer systems.

Full-time program: 2 years.

Part-time options: Limited

Distance learning options: Selected courses

University of California at Berkeley, Berkeley, California

Degree: Master of Engineering

School: College of Engineering, Electrical Engineering and Computer Sciences

Department

Description: Accelerated, interdisciplinary program has three major

components: a technical concentration, courses in leadership skills and a

"capstone" project through which teams of three to five students study a specific

problem or opportunity that can be addressed by technology. Concentration

options include Data Science and Systems, which prepares students for data-

centric industries requiring understanding of data management fundamentals,

technologies and techniques.

The College of Engineering is the home of Berkeley's AMPLab, which explores

the role of algorithms, machines and people in big data analytics.

Prerequisites: Bachelor's degree or equivalent with a minimum GPA of 3.0.

GRE test required.

Full-time program: 10 Months.

Part-time options: Yes. Two-year, part-time program available.

Distance learning options: No

University of Cincinnati, Cincinnati, Ohio

Degree: Master of Science in Business Analytics

School: Lindner College of Business

Description: Combines operations research and applied statistics, covering the

use of applied mathematics and computer applications in business. Formerly

known as MS -- Quantitative Analysis and taught by the Department of

Operations, Business Analytics and Information Systems, this program has been

evolving since the late 1970s. Relevant job-placement opportunities include

supply-chain management, manufacturing, operations, health-care analysis,

marketing research, financial risk analysis, information technology and

consulting.

Prerequisites: Undergraduate degree in any field is acceptable. Admission is

selective based on academic and professional achievement, performance on a

standardized tests (GRE or GMAT), communication skills and record of effective

leadership.

Full-time program: 9 months to 1 year.

Part-time options: Yes

Distance learning options: No

University of Connecticut, Graduate Learning Center, Hartford, Conn.

Degree: Master of Science in Business Analytics and Project Management

School: School of Business, Department of Operations and Information

Management

Description: Hybrid face-to-face and online program combining in-depth course

work in both advanced business analytics and project management along with a

broad choice of elective courses. Business analytics courses focus on data

development, storage, retrieval and utilization. Also covers data preparation,

predictive modeling, model assessment and model implementation as well as

decision analysis, optimization, simulation, sensitivity analysis, time-series

analysis and network modeling.

Project management courses focus on designing, managing and re-engineering

business processes; project management; project time, scope and quality

management; project communications management; project cost and risk

management; project procurement management; understanding leadership type,

behavioral strengths and motivators; influencing customers, managing team

collaboration and productivity, and change management.

Prerequisites: Undergraduate degree with a minimum GPA of 3.0. Completion

of a one-semester college-level calculus course. GMAT or GRE test.

Full-time program: 1 year.

Part-time options: Yes. Can be completed in 3.5 years.

Distance learning options: Selected courses.

University of Illinois, Champaign, Ill.

Degree: Master of Science in Statistics: Analytics Concentration

School: Graduate College, Department of Statistics

Description: Combines the mathematical and statistical training of a traditional

MS in Statistics with enhanced computational and data analytics training. The

program includes fundamentals in mathematical and applied statistics as well as

specialized training in data management, analysis and model building with large

datasets and databases. Specialized courses emphasize statistical computing,

data management and statistical learning, which encompasses topics under the

broader title of data mining.

MS applicants interested in careers in financial services or insurance are

encouraged to apply for the State Farm Research Center's Modeling and

Analytics Graduate Network program, which offers tuition support and internship

opportunities.

Prerequisites: Undergraduate degree (3.0+ GPA) with a background in

mathematics and statistics including calculus through multivariable calculus,

linear algebra and an introduction to mathematical statistics and probability. GRE

exam required. Students should have experience with computing and data,

including prior use of statistical software such as SAS or SPSS as well as an

interactive programming environment such as C, R or Matlab.

Full-time program: 1 Year (3 semesters).

Part-time options: Limited

Distance learning options: No

University of Ottawa, Ottawa, Ontario, Canada

Degree: Master in Electronic Business Technologies

Schools: Telfer School of Management, School of Information Technology and

Engineering, and the Faculty of Law.

Description: Interdisciplinary degree offering two specializations: Electronic

Business and Electronic Technologies. Electronic Business focuses on

organizational transformations based on IT, with research on best practices and

trends, comparative analysis of new business models, performance evaluation

based on new technologies, efficacy of new services and methods in attracting

and satisfying customers and simulation of integrated supply chains. Electronic

Technologies focuses on IT and system architectures used to create and

manage online transactions. Research focuses on electronic commerce

technologies and protocols (including wireless and multi-media); the analysis and

development of algorithms (including security, data mining, Web data

warehouses and distributed applications); and the definition of standards,

architectures and software engineering methodologies for e-commerce systems.

Analytics & Performance is one of three Strategic Areas of Excellence at the

Tefler School of Management. This focus is supported by the IBM Centre for

Business Analytics and Performance, which promotes research and curriculum

development in the domains of business analytics, business intelligence, and

performance management.

Prerequisites: Honors bachelor's degree in a relevant discipline. For the e-

business stream, disciplines such as business administration, economics,

computer science, electrical engineering and business information are relevant.

For the e-technologies stream, disciplines such as computer science, computer

engineering, software engineering, electrical engineering and business

information are relevant.

Full-time program: 12 months for a Master in Electronic Business Technologies;

16 months for a Master of Science in Electronic Business Technologies (thesis

required).

Part-time options: Yes, though degree must be completed within four years of

initial registration.

Distance learning options: Selected courses.

University of Tennessee, Knoxville, Tenn.

Degree: Master of Science in Business Analytics

School: College of Business Administration, Statistics, Operations &

Management Science

Description: Students develop the skills needed to work effectively in a business

environment while also gaining the analytic skills to solve business problems.

Core analytic skills are developed during the first year; students then choose one

of two overlapping areas as a concentration: applied statistics or process

optimization.

Prerequisites: Bachelor's degree with a GPA of 2.7+. If you have completed

previous graduate course work, you must have a GPA of 3.0+.

Full-time program: 2 years.

Part-time options: No

Distance learning options: No

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York University, Toronto, Ontario, Canada

Degree: Master of Science in Business Analytics

School: Schulich School of Business

Description: Develops quantitative and technical skills as well as communication

skills and the ability to transform data into a competitive asset. Program

concludes with a 12-week research project in which students focus on a hands-

on, research-driven problem within a company. Students gain advanced

statistical analysis skills and an understanding of customer and transactional

data. They'll also gain experience with big data, analytics and data visualization

tools. Finally, students will develop presentation and communication skills

needed to engage stakeholders on complex issues.

Prerequisites: Undergraduate degree (B+ average or better) in a field with

significant quantitative and computational requirements, such as commerce,

engineering, computer science, natural science, economics, mathematics or

statistics. GMAT test scores required (no more than 5 years old).

Full-time program: 1 year.

Part-time options: No

Distance learning options: No

Big Data Analytics Master's Degrees: 20

Top Programs These one-year and two-year graduate programs are just what's needed to close the big-data talent gap. Read on to find a school that fits your ambitions and background.

Arizona State University, Tempe, Ariz.

Master of Science In Business Analytics

Fordham University, New York, N.Y.

Master Of Science In Business Analytics

Kennesaw State University, Kennesaw, Ga.

Master of Science in Applied Statistics

Michigan State University, East Lansing, Mich.

Master of Science in Business Analytics

Purdue University, Lafayette, Ind.

Master of Business Administration, Business Analytics

Stevens Institute of Technology, Hoboken, N.J.

Master of Science -- Business Intelligence & Analytics

University of Maryland, College Park, Md.

Master of Science In Business: Marketing Analytics

University of Michigan-Dearborn, Dearborn, Mich.

Master of Science in Business Analytics

University of San Francisco, San Francisco, Cal.

Master of Science in Analytics

Virginia Commonwealth University, Richmond, Va.

Master of Science in Business, concentration in decision sciences and business

analytics