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.
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.
In this special, sponsored radio episode we’ll look at some terms around converged infrastructures and talk about how they’ve been applied in the past. Then we’ll turn to the present to see what’s changing.