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 Melbourne or in NobleProg corporate training centers in Melbourne.
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hu...
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hub, making it by far the most sought after address in the City. Positioned directly opposite the Bourke street Mall, the 41 level tower houses a two level retail complex, known as the Galleria Retail Centre. Showcased underneath an impressive high glass ceiling, the retail specialty stores offer the best in giftware, fashion, food and services. The premium grade property is uniquely positioned on a 45 degree angle to the Melbourne CBD grid, providing excellent 360 degree views and has excellent access to public transport, with trams running along both Bourke and Elizabeth Streets and train and bus stations within 500 metres.
Cliftons Perth
Parmelia House, 191 St Georges Terrace, Perth, Australia, 6000
Located within the historic Bishops See precinct, it sits at the western end of Perth’s Commercial Business District
In this instructor-led, live training in Melbourne, 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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