Online or onsite, instructor-led live kdb+ training courses demonstrate through interactive hands-on practice the fundamentals of kdb+.
kdb+ training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live kdb+ training can be carried out locally on customer premises in Vienna or in NobleProg corporate training centers in Vienna.
NobleProg -- Your Local Training Provider
NobleProg Wien
Modecenterstraße 22, Wien, Austria, 1030
Overview
Our training facilities are located at Modecenterstrasse 22 in Vienna. Our spaci...
Overview
Our training facilities are located at Modecenterstrasse 22 in Vienna. Our spacious training rooms offer optimal training conditions for your needs.
For questions and training registrations, please contact our company headquarters:
NobleProg Europe GmbH,
Kolonnenstr. 8
10827 Berlin
Deutschland
Directions
The NobleProg training facilities are conveniently located near the A23 motorway and the nearest subway station, within walking distance, is the Zippererstrasse station.
Parking spaces
There are parking spaces in the surrounding streets around our training rooms.
Local infrastructure
There are numerous restaurants within walking distance.
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
Audience
Developers
Database engineers
Data scientists
Data analysts
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
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