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.
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.