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 Maastricht or in NobleProg corporate training centers in Maastricht.
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.
In this instructor-led, live training in Maastricht, 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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