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 New Jersey or in NobleProg corporate training centers in New Jersey.
NobleProg -- Your Local Training Provider
NJ, Totowa - Riverview Drive
999 Riverview Drive, Totowa, united states, 07512
Totowa, NJ - The venue is located on the corner of Riverview Dr and Commerce Way.
NJ, Princeton - Overlook Business Center
100 Overlook Center, Princeton, united states, 08540
The venue is located just off Highway 1, in the vicinity of the American Red Cross of Central New Jersey and Wells Fargo Bank...
The venue is located just off Highway 1, in the vicinity of the American Red Cross of Central New Jersey and Wells Fargo Bank.
NJ, Newark - One Gateway Business Center
One Gateway Center Suite 2600, Newark, united states, 07102
Located in New Jersey, it is next to the Seton Hall University Law School and the Prudential Center, and a block from the pre...
Located in New Jersey, it is next to the Seton Hall University Law School and the Prudential Center, and a block from the prestigious New Jersey Performing Arts Center. The building is connected by covered walkway to Newark Penn making New York a short commute by PATH and giving good access to Boston and Washington DC.
In this instructor-led, live training in New Jersey, 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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