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 Manchester or in NobleProg corporate training centers in Manchester.
NobleProg -- Your Local Training Provider
Manchester
Oxford Street, Manchester, united kingdom, M1 5AN
DIRECTIONS
The office and training rooms are located under a 7 minute walk from Manchester Oxford Road Railway Sta...
DIRECTIONS
The office and training rooms are located under a 7 minute walk from Manchester Oxford Road Railway Station and a 10 minute walk from Deansgate Railway Station.
Peter House business center occupies a landmark building at a prominent central location in Manchester's established and vibrant business district, with city views overlooking Barbirolli Square and St. Peter's Square. A stunning central atrium fills the ground floor and reception with an abundance of natural light. The building is conveniently located with car parks, transport links and retail and leisure facilities on the doorstep. Recently ranked as the second best place to do business in the UK, the city is the UK's fifth largest financial center outside London. Manchester has a growing economy with many people (90,000) employed in financial services. It is also a centre for life sciences, professional services, creative, cultural and media, communications and manufacturing. The centre has 12 meeting rooms and conference suites.
In this instructor-led, live training in Manchester, 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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