225762967 Big Data Analytics Master

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
Recommended Reading
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