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 Namur can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Namur, Hotel de Ville
NobleProg Namur, Rue de Fer, 48 , Namur, Belgium, 5000
Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied...
Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied since the Neolithic period, the confluence of the Sambre and the Meuse saw the birth of the Roman city at the beginning of our era. Former stronghold of the Counts of Namur, attached to the house of Luxembourg and then to the Habsburg Empire, the citadel of Namur was the focus of many sieges over the years. Despite the damage suffered by the conflicts, the city retains a rich movable and immovable heritage. Today the regional capital, the city is the seat of the Parliament of Wallonia, the Walloon Government and the Public Service of Wallonia, but also the host city of the International Francophone Film Festival, the fairground arts festival Namur in May, the Festival Verdur Rock.
In this instructor-led, live training in Namur, 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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