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 Santiago or in NobleProg corporate training centers in Santiago.
The Center occupies the fifth and ninth floors of a modern office block with an attractive, spacious reception area. It has i...
The Center occupies the fifth and ninth floors of a modern office block with an attractive, spacious reception area. It has its own secure underground parking and is protected by 24-hour CCTV. It is just a few minutes' walk from an underground railway station. Arturo Meriono Benitez International Airport is 26km away.
The Santiago Vitacura Center is located on the 15th floor of one of the newest high-rise buildings in the city, situated near...
The Santiago Vitacura Center is located on the 15th floor of one of the newest high-rise buildings in the city, situated near El Bosque, an attractive business and residential district, and adjacent to the Santiago World Trade Center. The Center has its own on-site coffee bar and secure underground parking. There are good public transport connections, and the international airport is 40 minutes away.
In this instructor-led, live training in Santiago, 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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