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 Brighton or in NobleProg corporate training centers in Brighton.
NobleProg -- Your Local Training Provider
Brighton
3rd Floor, Queensberry House , Brighton, united kingdom, BN1 3XF
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping cen...
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping centre and the seafront. Queensberry House, which offers some sea views, is in the heart of the business district in this city. Brighton is a highly sophisticated and modern resort with a thriving economy and tourist industry. Millions of visitors flock here every year, both for leisure and to attend conferences and exhibitions at the Brighton Centre, one of the largest multi-purpose conference and exhibition centres in the country. Because it is home to so many businesses involved in media, particularly digital or 'new media', Brighton is sometimes referred to as 'Silicon Beach'. The city's priority sectors, which include financial services, creative industries and environmental technologies as well as digital media, are all growing steadily.
In this instructor-led, live training in Brighton, 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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