Amazon Web Services (AWS) - Big Data

Amazon Web Services - Big Data training will introduce participants into the world of Big Data processing using AWS platform. Course will cover practical knowledge about frameworks like Hadoop, Pig, Hive and AWS services, which enable processing of huge number of data in large, distributed clusters like EMR, DynamoDB, RedShift or Amazon Kinesis. And all this is based on interesting practical exercises.

Course agenda

  • Introduction
  • Public Compute Cloud and Big Data introduction
  • Amazon Web Services product suite supporting Big Data: EMR, Kinesis, DynamoDB i RedShift
  • Introduction to Hadoop, Hive, Pig and Streaming
  • Amazon Elastic MapReduce (Hadoop)
  • Introduction
  • MapReduce, Hadoop and HDFS
  • Architecture and Instance Groups
  • Instance types
  • Using Hive within EMR
  • Using Pig within EMR
  • Using Impala within EMR
  • Storing data with HBase
  • Data Visualization
  • Pricing
  • Amazon DynamoDB
  • Introduction
  • NoSQL
  • Data types and supported operations
  • Consistency
  • DynamoDB API
  • DynamoDB and Big Data, EMR integration
  • Pricing
  • Amazon Kinesis
  • Introduction
  • Kinesis and Big Data, integration with EMR
  • Configuration
  • Pricing
  • Amazon RedShift
  • Introduction
  • RedShift and Big Data
  • Configuration
  • Pricing
  • Amazon Cloud Watch
  • Introduction
  • CloudWatch Architecutre
  • Alarms and metrics
  • Using CloudWatch
  • Pricing
  • Test
  • Each training ends with test.
  • Training duration
  • 3 days
  • Available training locations
  • Kraków, Katowice, Wrocław
  • Training Mode
  • Lecture + Workshop
  • Paricipant profile and requirements
  • Training is designed for Big Data architects and developers. Programming and database knowledge is required. Java knowledge is recommended.
  • Benefits
  • After accomplishing the course participants will have hands-on knowledge about Big Data processing, MapReduce approach, EMR service, Hadoop, Pig and Hive. They will know how to provision Big Data environments and how to use DynamoDB, Redshift and Kinses for data processing.
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