Course Details

About This Course

kdb+ is an in-memory, column-oriented database and q is its built-in, interpreted vector-based language. In kdb+, tables are columns of vectors and q is used to perform operations on the table data as if it was a list. kdb+ and q are commonly used in high frequency trading and are popular with the major financial institutions, including Goldman Sachs, Morgan Stanley, Merrill Lynch, JP Morgan, etc. In this instructor-led, live training, participants will learn how to create a time series data application using kdb+ and q. By the end of this training, participants will be able to: Understand the difference between a row-oriented database and a column-oriented database. Select data, write scripts and create functions to carry out advanced analytics. Analyze time series data such as stock and commodity exchange data. Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed. Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages. Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring. Format of the Course Interactive lecture and discussion. Lots of exercises and practice. Hands-on implementation in a live-lab environment. Course Customization Options To request a customized training for this course, please contact us to arrange. This course is available as onsite live training in USA or online live training.

Duration: 21hrs

Venue: Online/Onsite