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. Poitiers onsite live GraphX trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Poitiers
NobleProg Poitiers, 21 rue Gaston Hulin, Poitiers, france, 86000
Training courses can be organised at our premises in Poitiers, at your premises, or remotely.
Training courses are given in...
Training courses can be organised at our premises in Poitiers, at your premises, or remotely.
Training courses are given in English or French. We organise a coordination meeting with the trainer and the participants to adapt the training program to your expectations. The courses consist of interactive discussions, theoretical parts and practical exercises.
The training is available as "live on-site training" or "live remote training". Live on-site training can be conducted locally at the client's premises in Poitiers or at the NobleProg corporate training centers in Poitiers.
Remote e-learning is conducted using an interactive desktop computer. NobleProg is the publisher of the DaDesktop software, which is presented in a video at https://www.dadesktop.com/
In this instructor-led, live training in Poitiers, 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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