Here’s a rundown of the 10 best graduate schools for Big Data, as ranked by informationweek.com.
[Editor’s note: This story is part of our end-of-year countdown, and was the 2nd most popular story on the site in 2014. Keep checking back every day as we build to our top story of 2014! Happy Holidays from eCampus News!]
If your favorite school did not make this list, please tell us why you think it should by commenting on this article, connecting with us on Twitter @ecampusnews.
1) Graduate School of Business, Bentley University–Waltham: “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.”
2) Heinz College (Public Policy & Information Systems), Carnegie Mellon University: “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.”
3) The Fu Foundation School of Engineering and Applied Science, Columbia University: “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.”
4) College of Computing and Digital Media, DePaul University: “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.”
5) LeBow College of Business, Drexel University: “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.”
6) School of Engineering and Applied Sciences, Harvard University: “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.”
7) E.J. Ourso College of Business, Louisiana State University: “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.”
7) The MIT Sloan School of Management, Massachusetts Institute of Technology: “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.”
8) Stern School of Business, New York University: “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.”
9) Institute for Advanced Analytics, North Carolina State University: “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.”
10) McCormick School of Engineering and Applied Science, Northwestern University: “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.”
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