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. Denver onsite live GraphX trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
CO, Denver - DTC Corporate Center III
7900 East Union Avenue Suite 1100, Denver, united states, 80237
The office in Denver Corporate is located at the heart of the Denver Tech Center - the district that is home to many of th...
The office in Denver Corporate is located at the heart of the Denver Tech Center - the district that is home to many of the city's major businesses and corporations. The Rocky Mountains can be seen from these 11th-floor offices, as well as the downtown skyline. The Denver Tech Center itself is strategically located at the junction between Interstates 225 and 25. It's minutes away from Belleview Light Rail station, with hotels and restaurants surrounding it. Its state-of-the-art office facilities come with beautiful mountain views.
In this instructor-led, live training in Denver, 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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