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. Maastricht onsite live kdb+ trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
The meeting rooms at Stationsplein in Maastricht are located in an inspiring high building with large windows to enjoy the vi...
The meeting rooms at Stationsplein in Maastricht are located in an inspiring high building with large windows to enjoy the view over this international city. Outside spraying fountains that provide a soothing environment to work. A number of national and international service companies have established themselves in this part of the Netherlands, and in the city there are also many large companies, including specialists in logistics, IT, medical and veterinary technologies and life sciences. There are also a number of large call centers here. Many important Dutch and European government offices are located in the city.
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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