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. Bilbao onsite live GraphX trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Bilbao
NobleProg Bilbao, Street Bikendi Kalea 5, Bizcaya, spain, 48001
Bilbao is a municipality located in the north of Spain, capital of the province and historical territory of Vizcaya, in the a...
Bilbao is a municipality located in the north of Spain, capital of the province and historical territory of Vizcaya, in the autonomous community of the Basque Country. The town of Bilbao is the capital and unique locality of the municipality, with 345 141 inhabitants.
Today it is a thriving city of services, which is in a process of aesthetic, social and economic revitalization led by the symbolic Guggenheim Museum Bilbao.
In addition to its airport, Bilbao has a large and effective line of railways and buses that circulate throughout the municipality.
In this instructor-led, live training in Bilbao, 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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