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 San José or in NobleProg corporate training centers in San José.
NobleProg -- Your Local Training Provider
San Jose - Plaza Roble Las Terrazas
Centro Corporativo Plaza Roble, San José, Costa rica
The San Jose Plaza Roble Las Terrazas Center is situated in one of six buildings connected by covered walkways that make up the secure Plaza Roble complex. With direct access to a major highway intersection, it is easy to get to downtown San Jose, 7km away, and a 15-minute drive to the international airport.
San Jose - Boulevard Dent
6184 Boulevard Dent San Jose San Pedro , San Jose, Costa rica, 11501
Create a fresh headquarters for your company in Costa Rica, featuring fully equipped office facilities at 6184 Boulevard Dent. Dive right into operations in the rapidly expanding capital, situated within the vibrant business hub of The Alameda. Benefit from convenient access to public transportation via bus and train for commuting, as well as the attractions of Downtown San Jose.
In this instructor-led, live training in San José, 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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