Slideshows

Big Data Analytics Master's Degrees: 20 Top Programs

Doug Henschen January 08, 2013 09:06 AM 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.

« Previous Page | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Next Page »

Big Data Analytics Master's Degrees: 20 Top Programs

E-mail
Share

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.

Recommended Reading

Big Data Talent War: 7 Ways To Win

13 Big Data Vendors To Watch In 2013

5 Big Data Predictions For 2013

Big Data Topic Center

Should You Outsource Your Data Scientist?

Big Data Revolution Will Be Led By Revolutionaries

Kaggle Crowdsources The Data Scientist Problem

Future Power Grids Will Need Big Data Analysis

Research: Big Data, Smart Data

Research: 2012 Big Data and Analytics Staffing Survey

« Previous Page | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Next Page »

By The Numbers

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?

SaS

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.