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 Nagoya or in NobleProg corporate training centers in Nagoya.
Nagoya is the third largest city in Japan. This open office is located in the district surrounding Nagoya station. Since 2015...
Nagoya is the third largest city in Japan. This open office is located in the district surrounding Nagoya station. Since 2015, landmark buildings kept inaugurating around the station and by 2017, it is predictable that many corporations will choose to be in this Meieki area. Furthermore, with the magnetic-levitated linear shinkansen to start service in 2027, Nagoya has strategic advantage.
Nagoya and Aichi area is known for its auto industry like Toyota. Besides automobiles, there are many head offices of Japanese manufacturers. With their affiliated companies and partners located in the same area, the city itself is a business complex. In recent years, forward-thinking IT companies are also trying to get a foothold in Nagoya. Besides all the attention-gathering news on the redevelopment, Meieki area has good access to Tokyo, Osaka and other major cities. It is also convenient for sales activity and commute. Therefore, it is a popular yet practical business district.
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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