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 Hsinchu or in NobleProg corporate training centers in Hsinchu.
NobleProg -- Your Local Training Provider
The Hsinchu Wishun centre
HSR Hsinchu Station District Lots, 6/F, No.46 and No.47 in ShiHsin Section, Hsinchu, taiwan, 30274
The Hsinchu Wishun centre is located in the commercial area of Hsinchu THSR district. It only takes 1 minute walk to Hsinchu ...
The Hsinchu Wishun centre is located in the commercial area of Hsinchu THSR district. It only takes 1 minute walk to Hsinchu HSR station which is connected to the centre building and Train Neiwan line. With its convenient transport connectivity, it is also easy to access through National Highway No.1 and Expressway to Hsinchu Science Park (8km) and Hsinchu CBD (15km ).
The centre is located at one of the very few grade A buildings in Hsinchu. The newly constructed building is with abundant local amenities, including restaurants, retail shops, recreation facilities and a hotel. Nearby parks and hotels include Shuizhen Forest Park and Hsinchu Sheraton hotel. Surrounded by hi-tech companies and high end residential communities, the location is a new hub for companies that are looking to grow and start their business in Hsinchu. Regus Hsinchu Wishun centre offers flexible workplace solutions to accommodate needs of all types and sizes with comprehensive services at a reasonable price.
In this instructor-led, live training in Hsinchu, 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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