Class Description
This 3-day class introduces Participants to cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis and the rest of the AWS big data platform. In this course, we show Participants how to use Amazon EMR to process data using the broad ecosystem of Hardtop tools like Hive and Hue. We also teach Participants how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.
Course Benefits
- 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
Suggested Prerequisites
- Basic familiarity with big data technologies, including Apache Hadoop, MapReduce, and 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
Course Outline
- 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
- Hadoop Programming Frameworks
- Processing Server Logs with Hive on Amazon EMR
- Processing Chemistry Data Using Hadoop Streaming on Amazon EMR
- Streamlining Students Amazon EMR Experience with Hue
- Running Pig Scripts with 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 Students Amazon EMR Deployments
- Data Warehouses and Columnar Datastores
- Amazon Redshift and Big Data
- Optimizing Students Amazon Redshift Environment
- Big Data Design Patterns
- Visualizing and Orchestrating Big Data
- Using Tibco Spotfire to Visualize Big Data
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- AWS 101 – AWS Business Essentials
- AWS 110 – AWS Technical Essentials
- AWS 201 – Architecting on AWS
- AWS 210 – Advanced Architecting on AWS
- AWS 220 – Certification Exam Readiness Workshop: Certified Solutions Architect – Associate
- AWS 230 – Certification Exam Readiness Workshop: Certified Solutions Architect – Professional
- AWS 301 – Developing on AWS
- AWS 410 – Systems Operations on AWS
Our goal is to make sure your class meets your objectives, not ours. Therefore, all of our outlines are treated as guides to help steer the workshop. This outline does not guarantee that all the topics listed will be covered in the time allowed. The amount of material covered is based on the skill level of the student audience. We may change or alter course topics to best suit the classroom situation.
Locations