Online or onsite, instructor-led live GraphX training courses demonstrate through hands-on practice how to implement GraphX to carry out graph computing across many machines in parallel.
GraphX 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 GraphX training can be carried out locally on customer premises in Rotterdam or in NobleProg corporate training centers in Rotterdam.
NobleProg -- Your Local Training Provider
Rotterdam
Novotel Rotterdam Brainpark, K.P. van der Mandelelaan 150, Rotterdam, Netherlands, 3062 MB
The meeting rooms in Brainpark in Rotterdam are located at one of the most prestigious business addresses of the city, on the...
The meeting rooms in Brainpark in Rotterdam are located at one of the most prestigious business addresses of the city, on the most famous business park in Rotterdam. Among the locally established companies are international and smaller specialized companies in the service sector, mainly financial, consultancy and cargo-related services, which shows the importance of Rotterdam as an international deep-water sea and river port, the gateway to European markets for a wide selection industrial and consumer products.
In this instructor-led, live training in Rotterdam, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a Graph Computing (also known as Graph Analytics) approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments.
By the end of this training, participants will be able to:
Understand how graph data is persisted and traversed.
Select the best framework for a given task (from graph databases to batch processing frameworks.)
Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
View real-world big data problems in terms of graphs, processes and traversals.
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