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. Brugge onsite live GraphX trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Bruges
NH Hotel Bruges, Boeveriestraat 2, Bruges, Belgium, 8000
Bruges became a central port, commercial and financial hub in medieval Europe, linking the countries of the North Sea and ...
Bruges became a central port, commercial and financial hub in medieval Europe, linking the countries of the North Sea and the Baltic to the Mediterranean. Wealthy merchants from Bruges traded with those from all over Europe. The first stock exchange in history was born in Bruges in the 13th century. In the 15th century it was the leading financial center in Europe. This economic boom also leads to a cultural and artistic flowering that has left an abundant heritage. It was the most important center for the Flemish primitive painters, who revolutionized Western painting. It has been a member of the Organization of World Heritage Cities since the year 2000. The city even has the distinction of appearing three times on the UNESCO World Heritage List. For its historic center, for its beguinage which is part of the Flemish Beguinages and for its belfry included among the Belfries of Belgium and France. In addition, it is also listed as Intangible Cultural Heritage of Humanity by UNESCO for its Procession of the Holy Blood.
In this instructor-led, live training in Brugge, 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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