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 trainings in The Hague can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
The Hague
The Office Operators , Schenkkade 50, The Hague, Netherlands, 2595 AR
Attend training courses at a top location in the business district of The Hague with Professional and modern meeting rooms fi...
Attend training courses at a top location in the business district of The Hague with Professional and modern meeting rooms fitted to your needs, with excellent accessibility. The Haagsche Zwaan has it all.
In the center just a few minutes away from the train station Den Haag Laan van NOI and the exit 3 of highway A12 you will find De Haagse Zwaan. Train and metro (line E The Hague Central or Laan NOI) are at 8 minutes walking distance. Tram stop Beatrixkwartier for the Randstadrail line 3 and 4 is at a 3 minute walk.
In this instructor-led, live training in The Hague, 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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