Building Streaming Data Analytics Solutions on AWS

1 day

English

In Kooperation mit

Learn to design and implement streaming data analytics solutions using AWS Services with an expert AWS instructor.

Content

The course dives deep into Amazon Kinesis and Amazon MSK through a mixture of instructor-led presentations, practice labs, demonstrations, and class exercises so you can walk away understanding how to build a streaming data analytics solution on AWS. You'll also learn how to scale streaming applications using Amazon Kinesis, optimize data storage, how to select and deploy appropriate options to ingest, transform, store, and analyze data, and more.

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
Demo: 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
Demo: 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
Demo: 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
Demo: Scaling up Amazon MSK storage
Practice Lab: Amazon MSK streaming pipeline and application deployment
Security and monitoring
Demo: 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

Benefits

Understanding the features and benefits of a modern data architecture. Learn how AWS streaming services fit into a modern data architecture.
Designing and implementing a streaming data analytics solution
Identifying and applying appropriate techniques, such as compression, sharding, and partitioning, to optimize data storage
Selecting and deploying appropriate options to ingest, transform, and store real-time and near real-time data
Choosing the appropriate streams, clusters, topics, scaling approach, and network topology for a particular business use case
Understanding how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
Securing streaming data at rest and in transit
Monitoring analytics workloads to identify and remediate problems
Applying cost management best practices

IMPORTANT: This course prepares you for the AWS Data Analytics Certification, among other courses in the Data Analytics job role track.

Instructor

Yuri Nikulin

Methods

This course includes instructor lecture, presentations, hands-on labs, demonstrations, and group exercises/discussions.

Who should attend

This course is intended for the following job roles:

Data Analytics

We recommend that attendees of this course have the following prerequisites:

a minimum one-year experience managing data analytics solutions or streaming data
and have attended the following course (or have equivalent knowledge): Building Batch Data Analytics Solutions on AWS