
Lokální instruktorem vedené kdb+ školení České republice.
Reference
The Trainer Subject Knowledge
Rares Serea - eMAG IT Research
Kurz: Which data storage to choose - from flat files, through SQL, NoSQL to massive distributed systems
I liked that he had actual know how of when to use each technology, that's valuable.
Radu Mazilu - eMAG IT Research
Kurz: Which data storage to choose - from flat files, through SQL, NoSQL to massive distributed systems
kdb+ Návrh Školení
Název školení
Doba trvání
Přehled
Název školení
Doba trvání
Přehled
21 hodin
Přehled
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
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
21 hodin
Přehled
Audience
*KDB+/Q developer
Format of the course
50% lectures, 40% labs, 10% tests
*KDB+/Q developer
Format of the course
50% lectures, 40% labs, 10% tests
Ostatní regiony
Ostatní země
Konzultace
Víkendové kdb+ kurzy, Večerní kdb+ školení, kdb+ přijímač, kdb+ vedené školitelem, Víkendové kdb+ školení, Večerní kdb+ kurzy, kdb+ koučování, kdb+ lektor, kdb+ školitel, kdb+ počítačová školení, kdb+ počítačové kurzy , kdb+ kurzy, kdb+ školení, kdb+ on-site, kdb+ uzavřená školení, kdb+ individuální školení






























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