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 trainings in Edinburgh can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Edinburgh
83 Princes Street , Edinburgh, united kingdom, EH2 2ER
The training rooms is located under a 10 minute walk from Edinburgh Rail Station
This centre's location on Edinburg...
The training rooms is located under a 10 minute walk from Edinburgh Rail Station
This centre's location on Edinburgh's world-famous Princes Street takes some beating. Right in the centre of Scotland's capital city, these prestigious business premises are spread across six floors with fantastic views over Princes Street Gardens towards the Royal Mile and Edinburgh Castle. As well as having all the usual amenities of a major city on its doorstep, the building also has a car park. Prosperous Edinburgh is a global centre for business, science, education and the arts and is said to have the strongest economy of any UK city outside London. Banking has been a part of the economic life of Edinburgh for over 300 years and today it is the UK's second financial centre after London and Europe's fourth by equity assets. Tourism, financial services and banking are particularly important employers as well as education, the public sector and hi-tech research and development.
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In this instructor-led, live training in Edinburgh, 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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