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Big Data on AWS

WGAC-AWS-BDAWS

Amazon Web Services Training Courses Certification

Schedule

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Open
Amazon Web Services

Big Data on AWS

WGAC-AWS-BDAWS

Zurich

Language: German

CET UTC+01:00

Start date:26 Sep 2022 09:00
End date:28 Sep 2022 17:00
Duration:3 days

$ 2,390

Open
Amazon Web Services

Big Data on AWS

WGAC-AWS-BDAWS

Berlin

Language: German

CET UTC+01:00

Start date:26 Oct 2022 10:00
End date:28 Oct 2022 17:00
Duration:3 days

$ 2,685

Open
Amazon Web Services

Big Data on AWS

WGAC-AWS-BDAWS

Virtual ILT

Language: Polish

CET UTC+01:00

Start date:04 Nov 2022 09:00
End date:06 Nov 2022 17:00
Duration:3 days

$ 5,500

Open
Amazon Web Services

Big Data on AWS

WGAC-AWS-BDAWS

Zurich

Language: German

CET UTC+01:00

Start date:07 Nov 2022 09:00
End date:09 Nov 2022 17:00
Duration:3 days

$ 2,390

Open
Amazon Web Services

Big Data on AWS

WGAC-AWS-BDAWS

London, City

Language: English

GMT UTC+00:00

Start date:28 Nov 2022 09:00
End date:30 Nov 2022 17:00
Duration:3 days

$ 2,100

Description

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 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 course or have equivalent experience
  • Basic understanding of data warehousing, relational database systems, and database design

This course teaches you how to:

  • Fit AWS solutions inside of a big data ecosystem
  • Leverage Apache Hadoop in the context of Amazon EMR
  • Identify the components of an Amazon EMR cluster
  • Launch and configure an Amazon EMR cluster
  • Leverage common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming
  • Leverage Hue to improve the ease-of-use of Amazon EMR
  • Use in-memory analytics with Spark and Spark SQL on Amazon EMR
  • Choose appropriate AWS data storage options
  • Identify the benefits of using Amazon Kinesis for near real-time big data processing
  • Define data warehousing and columnar database concepts
  • Leverage Amazon Redshift to efficiently store and analyze data
  • Comprehend and manage costs and security for Amazon EMR and Amazon Redshift deployments
  • Identify options for ingesting, transferring, and compressing data
  • Use visualization software to depict data and queries
  • Orchestrate big data workflows using AWS Data Pipeline

Day 1
  • Overview of Big Data
  • Ingestion, Transfer, and Compression
  • Storage Solutions
  • Storing and Querying Data on DynamoDB
  • Big Data Processing and Amazon Kinesis
  • Introduction to Apache Hadoop and Amazon EMR
  • Using Amazon Elastic MapReduce
Day 2
  • Hadoop Programming Frameworks
  • Processing Server Logs with Hive on Amazon EMR
  • Processing Chemistry Data Using Hadoop Streaming on Amazon EMR
  • Streamlining Your Amazon EMR Experience with Hue
  • Running Pig Scripts in Hue on Amazon EMR
  • Spark on Amazon EMR
  • Interactively Creating and Querying Tables with Spark and Spark SQL on Amazon EMR
  • Managing Amazon EMR Costs
  • Securing your Amazon EMR Deployments
Day 3
  • Data Warehouses and Columnar Datastores
  • Amazon Redshift and Big Data
  • Optimizing Your Amazon Redshift Environment
  • Big Data Design Patterns
  • Visualizing and Orchestrating Big Data
  • Using Tibco Spotfire to Visualize Big Data
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