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.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
Top IT Trends to Watch in Financial ServicesIT pros at banks, investment houses, insurance companies, and other financial services organizations are focused on a range of issues, from peer-to-peer lending to cybersecurity to performance, agility, and compliance. It all matters.
Join us for a roundup of the top stories on InformationWeek.com for the week of October 9, 2016. We'll be talking with the InformationWeek.com editors and correspondents who brought you the top stories of the week to get the "story behind the story."