Building Systems for Big Data Analytics: From SQL to Machine Learning and Graph Analysis
published: Dec. 1, 2017, recorded: August 2017, views: 771
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Big data is being generated everywhere at all times. It has become more and more important to analyze the large volume of data to drive actionable insights. There are different types of analytics that can exploit the wealth of information in big data, from traditional business analytics using SQL to complex machine learning and graph analysis. In this keynote, Dr. Tian will share her experience and lessons learned in building different types of analytics systems for big data. In particular, this talk will feature her work on studying distributed join algorithms for SQL-on-Hadoop systems, building the large-scale machine learning system SystemML, and inventing new processing models for distributed graph processing.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !