DC, Washington - Street Northwest

20 F Street Northwest, Washington, United States, 20001
The Center is located on Capitol Hill, one block from Union Station Metro and 15 minutes from Washington Reagan National Airp...

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Introduction to Graph Computing

28 Hours
In this instructor-led, live training in Washington D.C., 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 (15)

Ernesto did a great job explaining the high level concepts of using Spark and its various modules.

Michael Nemerouf
Course - Spark for Developers

Having hands on session / assignments

Poornima Chenthamarakshan - Intelligent Medical Objects
Course - Apache Spark in the Cloud

1. Right balance between high level concepts and technical details. 2. Andras is very knowledgeable about his teaching. 3. Exercise

Steven Wu - Intelligent Medical Objects
Course - Apache Spark in the Cloud

La combinación de teoría y práctica con herramientas como databricks

Graciela Saud - Servicio de Impuestos Internos
Course - Spark for Developers

Doing similar exercises different ways really help understanding what each component (Hadoop/Spark, standalone/cluster) can do on its own and together. It gave me ideas on how I should test my application on my local machine when I develop vs when it is deployed on a cluster.

Thomas Carcaud - IT Frankfurt GmbH
Course - Spark for Developers

Ajay was very friendly, helpful and also knowledgable about the topic he was discussing.

Biniam Guulay - ICE International Copyright Enterprise Germany GmbH
Course - Spark for Developers

Sufficient hands on, trainer is knowledgable

Chris Tan
Course - A Practical Introduction to Stream Processing

The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.

Safar Alqahtani - Elm Information Security
Course - Big Data Analytics in Health

very interactive...

Richard Langford
Course - SMACK Stack for Data Science

Commitment and willingness to explain secondary topics.

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

Machine Translated

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

Machine Translated

Exercises and exchanges during questions/answers

Antoine - Physiobotic
Course - Scaling Data Pipelines with Spark NLP

Machine Translated

The good humor, support and skills of the trainer.

Oumayma - Physiobotic
Course - Scaling Data Pipelines with Spark NLP

Machine Translated

The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.

Raul Mihail Rat - Accenture Industrial SS
Course - Python, Spark, and Hadoop for Big Data

I liked that it managed to lay the foundations of the topic and go to some quite advanced exercises. Also provided easy ways to write/test the code.

Ionut Goga - Accenture Industrial SS
Course - Python, Spark, and Hadoop for Big Data

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