AMA18 – Building Data Analytics Solutions Using Amazon Redshift
AMA20 - Building Streaming Data Analytics Solutions on AWS
Course description
In this course, you will learn to build streaming data analytics solutions using AWS services, including
Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a massively scalable and durable real-time data streaming service. Amazon MSK offers a secure, fully managed, and highly available Apache Kafka service. You will learn how Amazon Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda. The course addresses the streaming data
ingestion, stream storage, and stream processing components of the data analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Kinesis and Amazon MSK.
Activities
This course includes presentations, practice labs, discussions, and class exercises.
Course objectives
In this course, you will learn to:
Understand the features and benefits of a modern data architecture. Learn how AWS streaming services fit into a modern data architecture.
Design and implement a streaming data analytics solution
Identify and apply appropriate techniques, such as compression, sharding, and partitioning, to optimize data storage
Select and deploy appropriate options to ingest, transform, and store real-time and near real-time data
Choose the appropriate streams, clusters, topics, scaling approach, and network topology for a particular business use case
Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
Secure streaming data at rest and in transit
Monitor analytics workloads to identify and remediate problems
Apply cost management best practices
Intended audience
This course is intended for:
Data engineers and architects
Developers who want to build and manage real-time applications and streaming data analytics solutions
AWS Classroom Training
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Prerequisites
We recommend that attendees of this course have:
At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions.
We suggest the Streaming Data Solutions on AWS whitepaper for those that need a refresher on streaming concepts.
Completed either Architecting on AWS or Data Analytics Fundamentals
Completed Building Data Lakes on AWS
Enroll today
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Course outline
Module A: Overview of Data Analytics and the Data Pipeline
Data analytics use cases
Using the data pipeline for analytics
Module 1: Using Streaming Services in the Data Analytics Pipeline
The importance of streaming data analytics
The streaming data analytics pipeline
Streaming concepts
Module 2: Introduction to AWS Streaming Services
Streaming data services in AWS
Amazon Kinesis in analytics solutions
Demonstration: Explore Amazon Kinesis Data Streams
Practice Lab: Setting up a streaming delivery pipeline with Amazon Kinesis
Using Amazon Kinesis Data Analytics
Introduction to Amazon MSK
Overview of Spark Streaming
Module 3: Using Amazon Kinesis for Real-time Data Analytics
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: Streaming analytics with Amazon Kinesis Data
Analytics and Apache Flink
Module 4: Securing, Monitoring, and Optimizing Amazon Kinesis
Optimize Amazon Kinesis to gain actionable business insights
Security and monitoring best practices
Module 5: Using Amazon MSK in Streaming Data Analytics Solutions
Use cases for Amazon MSK
Creating MSK clusters
Demonstration: Provisioning an MSK Cluster
Ingesting data into Amazon MSK
Practice Lab: Introduction to access control with Amazon MSK
Transforming and processing in Amazon MSK
Module 6: Securing, Monitoring, and Optimizing Amazon MSK
Optimizing Amazon MSK
Demonstration: Scaling up Amazon MSK storage
Practice Lab: Amazon MSK streaming pipeline and application deployment
Security and monitoring
Demonstration: Monitoring an MSK cluster
Module 7: Designing Streaming Data Analytics Solutions
Use case review
Class Exercise: Designing a streaming data analytics workflow
Module B: Developing Modern Data Architectures on AWS
Modern data architectures