Kaminia

P.E.O., Patron Pyrgos 608 B, Kaminia , Greece, 25002

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Introduction to Graph Computing

 28 Hours
In this instructor-led, live training in Patras, 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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Testimonials (4)

Exercises and exchanges during questions/answers

Antoine - Physiobotic
Course - Scaling Data Pipelines with Spark NLP

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The good humor, support and skills of the trainer.

Oumayma - Physiobotic
Course - Scaling Data Pipelines with Spark NLP

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Commitment and willingness to explain secondary topics.

Marek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Course - Apache Spark Fundamentals

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The trainer's practical experience, not coloring the discussed solution, but also not introducing a negative connotation. I feel that the trainer is preparing me for real and practical use of the tool - these valuable details are usually not found in books.

Krzysztof Miodek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Course - Apache Spark Fundamentals

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