Online or onsite, instructor-led live Apache Arrow training courses demonstrate through interactive hands-on practice how to use Apache Arrow to process data from disparate data sources..
Apache Arrow 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 Apache Arrow training can be carried out locally on customer premises in Antwerp or in NobleProg corporate training centers in Antwerp.
NobleProg -- Your Local Training Provider
Antwerp
Hotel NH Collection Antwerp Centre, Pelikaanstraat 84, 2018 Antwerpen, Belgium, Antwerp, Belgium, 2018
The hotel has a conference capacity for up to 110 attendees, with 6 dedicated, flexible spaces available. A range of smaller...
The hotel has a conference capacity for up to 110 attendees, with 6 dedicated, flexible spaces available. A range of smaller boardrooms and a larger conference room is available for large and small meetings. The facilities include up-to-date audio-visual equipment, with refreshments available to order and an events planner on site for assistance. Unusually for a city center hotel, the hotel offers parking in its own garage.
Apache Arrow is an open-source in-memory data processing framework. It is often used together with other data science tools for accessing disparate data stores for analysis. It integrates well with other technologies such as GPU databases, machine learning libraries and tools, execution engines, and data visualization frameworks.
In this onsite instructor-led, live training, participants will learn how to integrate Apache Arrow with various Data Science frameworks to access data from disparate data sources.
By the end of this training, participants will be able to:
Install and configure Apache Arrow in a distributed clustered environment
Use Apache Arrow to access data from disparate data sources
Use Apache Arrow to bypass the need for constructing and maintaining complex ETL pipelines
Analyze data across disparate data sources without having to consolidate it into a centralized repository
Audience
Data scientists
Data engineers
Format of the Course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
To request a customized training for this course, please contact us to arrange.
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