School: School of Engineering, Computer Science Department
Description: Covers the principles of modern database and information management systems as well as methods for mining massive data sets. Topics range from system design, architecture and management to applying algorithms, data-mining and machine-learning techniques to perform analyses over large data sets. Related topics include distributed systems, networking and security on the system side as well as text mining, bioinformatics, Web search and social media applications.
Prerequisites: Candidates must have acquired the foundations of computer science at the level of an undergrad minor at a minimum. At Stanford these foundations include courses on the mathematical foundations of computing, programming methodology and abstractions, computer organization and systems, object-oriented systems design and principles of computer systems.
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.