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Programm

  1. Overview of Big Data

  2. Big Data Ingestion and Transfer

  3. Big Data Streaming and Amazon Kinesis


    1. Lab 1: Using Amazon Kinesis to Stream and Analyze Apache Server Log Data


  4. Big Data Storage Solutions

  5. Big Data Processing and Analytics


    1. Lab 2: Using Amazon Athena to Query Log Data From Amazon S3


  6. Apache Hadoop and Amazon EMR


    1. Lab 3: Storing and Querying Data on Amazon DynamoDB


  7. Using Amazon EMR

  8. Hadoop Programming Frameworks


    1. Lab 4: Processing Server Logs With Hive on Amazon EMR


  9. Web Interfaces on Amazon EMR


    1. Lab 5: Running Pig Scripts in Hue on Amazon EMR


  10. Apache Spark on Amazon EMR


    1. Lab 6: Processing NY Taxi data using Spark on Amazon EMR


  11. Amazon Redshift and Big Data

  12. Visualizing and Orchestrating Big Data


    1. Lab 7: Using TIBCO Spotfire to Visualize Data


  13. Managing Big Data Costs

  14. Securing Your Amazon Deployments

  15. Big Data Design Patterns


Ziele
Big Data on AWS introduces you to cloud-based big data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis and the rest of the AWS big data platform. In this course, we show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue.

We also teach you how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, Amazon Quicksight, Amazon Athena and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.



.... Course Description
Voraussetzungen
We recommend that attendees of this course have the following prerequisites:

  • Basic familiarity with big data technologies, including Apache Hadoop, MapReduce, HDFS, and SQL/NoSQL querying

  • Students should complete the free Big Data Technology Fundamentals web-based training or have equivalent experience

  • Working knowledge of core AWS services and public cloud implementation

  • Students should complete the AWS Technical Essentials course or have equivalent experience

  • Basic understanding of data warehousing, relational database systems, and database design