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 Kuala Lumpur or in NobleProg corporate training centers in Kuala Lumpur.
NobleProg -- Your Local Training Provider
Kuala Lumpur KL Sentral
1 Sentral, Level 16, Jalan , Kuala Lumpur, malaysia, 50470
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. A...
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. Although 1 Sentral is just outside the central business district, Kuala Lumpur Sentral is known as a transportation hub and as one of the designated Multimedia Supercorridor (MSC) locations. A Government designated zone, the MSC is designed to leapfrog Malaysia into the information and knowledge age. The zone aims to attract companies with tax breaks and facilities such as high speed internet and proximity to the local international airport. 1 Sentral is a 30-storey office tower covering an acre and is equipped with facilities such as mini auditorium, gymnasium and recreational area. Its architecture has integrated a variety of design techniques that make it eco-friendly and aesthetically-pleasing. Restaurants, top hotels and shopping centres are all within a five- to 10-minute walk from the centre
In this instructor-led, live training in Kuala Lumpur, 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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