Building Streaming Data Analytics Solutions on AWS - Course Overview

Through a combination of instructor-led presentations, practice labs, demonstrations, and in-class exercises, the course delves deeply into Amazon Kinesis and Amazon MSK so that you can leave with an understanding of how to create a streaming data analytics solution on AWS. Along with these skills, you’ll learn how to use Amazon Kinesis and Amazon MSK to scale streaming applications, optimize data storage, choose and implement the best options for ingesting, transforming, storing, and analyzing data.

After completing Building Streaming Data Analytics Solutions on AWS, students will be able to

  • Create and implement a streaming data analytics solution on AWS.
  • Examine and contrast the features and advantages of data lakes, data warehouses, and modern data architecture.
  • Determine and use the best methods, such as compression, to maximize data storage Understanding how data processing and storage affect the analysis and visualization mechanisms required to obtain actionable business insights. Determining the appropriate data streams, clusters, topics, scaling, and network topology for a given business use case. Selecting and implementing the right options to ingest, transform, and store real-time and near real-time data.
  • Safeguard data both in transit and at rest; keep an eye on analytics workloads to spot issues and fix them; and use best practices for cost management.

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Building Streaming Data Analytics Solutions on AWS - Key Features

  • Building Streaming Data Analytics Solutions on AWS offers several key features, including:

  • Comprehensive Curriculum: The course covers major aspects of streaming services on AWS.

  • Participants will have the opportunity to practice hands-on labs.

  • Experienced Instructors: The course is taught by AWS Authorized Instructors with years of experience in AWS, ensuring high-quality instruction.

  • Flexible Schedule: The course is offered in both online and in-person formats, with options for full-time or part-time study.

Who should attend this Course?

  • Data engineers.
  • Developers.
  • Data Platform engineers.
  • Architects and operators who build and manage data pipeline.

Prerequisites -

  • Participant who has minimum of 1 year experience managing data analytics solutions and streaming data analytics solutions.
  • Participant must have undergone either AWS Technical Essentials or Architecting on AWS course.
  • Completed Building Data Lakes on AWS course.

    Building Streaming Data Analytics Solutions on AWS - Course Outline Download Course Outline

    • Data analytics use cases
    • Using the data pipeline for analytics

    • The importance of streaming data analytics
    • The streaming data analytics pipeline
    • Streaming concepts

    • Streaming data services in AWS
    • Amazon Kinesis in analytics solutions
    • Demonstration: Explore Amazon Kinesis Data Streams
    • Practice Lab 1: Setting up a streaming delivery pipeline with Amazon Kinesis
    • Using Amazon Kinesis Data Analytics
    • Introduction to Amazon MSK
    • Overview of Spark Streaming

    • Exploring Amazon Kinesis using a clickstream workload
    • Creating Kinesis data and delivery streams
    • Demonstration: Understanding producers and consumers
    • Building stream producers
    • Building stream consumers
    • Building and deploying Flink applications in Kinesis Data Analytics
    • Demonstration: Explore Zeppelin notebooks for Kinesis Data Analytics
    • Practice Lab 2: Streaming analytics with Amazon Kinesis Data Analytics and Apache Flink

    • Optimize Amazon Kinesis to gain actionable business insights
    • Security and monitoring best practices

    • Use cases for Amazon MSK
    • Creating MSK clusters
    • Demonstration: Provisioning an MSK Cluster
    • Ingesting data into Amazon MSK
    • Practice Lab 3: Introduction to access control with Amazon MSK
    • Transforming and processing in Amazon MSK

    • Optimizing Amazon MSK
    • Demonstration: Scaling up Amazon MSK storage
    • Practice Lab 4: Amazon MSK streaming pipeline and application deployment
    • Security and monitoring
    • Demonstration: Monitoring an MSK cluster

    • Use case review
    • Class Exercise: Designing a streaming data analytics workflow

    • Modern data architectures

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    Course ID: 20043

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