Building Streaming Data Analytics Solutions on AWS

In this course, you will learn how to build streaming data analytics solutions using AWS services such as Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). The course focuses on designing, implementing, securing, and operating real-time and near real-time analytics pipelines on AWS.

This instructor-led training covers streaming data ingestion, stream storage, and stream processing within modern data analytics architectures. You work with Amazon Kinesis and Amazon MSK and learn how these services integrate with AWS Glue, AWS Lambda, and other AWS services. The course also addresses security, performance, and cost management best practices for streaming analytics workloads.

Course objectives

In this course, you will learn to:

Understand the role of streaming services in modern data architectures
Design and implement streaming data analytics solutions
Optimise data storage using techniques such as compression, sharding, and partitioning
Select and deploy appropriate options to ingest, transform, and store real-time and near real-time data
Choose suitable streams, clusters, topics, scaling approaches, and network topologies
Understand how data storage and processing affect analytics and visualisation
Secure streaming data at rest and in transit
Monitor analytics workloads and remediate issues
Apply cost management best practices

Prerequisites

We recommend that attendees of this course have:

At least one year of data analytics experience or experience building real-time or streaming analytics solutions
Completed either Architecting on AWS or Data Analytics Fundamentals
Completed Building Data Lakes on AWS

Target audience

This course is intended for:

Data engineers and architects
Developers building and managing real-time applications and streaming data analytics solutions

Overview of data analytics and the data pipeline

You are introduced to analytics use cases and how streaming fits into the data analytics pipeline.

Using streaming services in analytics

This section covers streaming concepts, the importance of streaming analytics, and how streaming services are used within analytics pipelines.

Introduction to AWS streaming services

You explore Amazon Kinesis and Amazon MSK, including demonstrations and hands-on labs setting up streaming delivery pipelines.

Real-time analytics with Amazon Kinesis

You work with Kinesis Data Streams and Kinesis Data Analytics, build producers and consumers, and develop streaming applications using Apache Flink.

Securing, monitoring, and optimising Amazon Kinesis

The course covers optimisation techniques, security practices, and monitoring approaches for Kinesis workloads.

Using Amazon MSK for streaming analytics

You learn how to design and deploy streaming solutions using Amazon MSK, including cluster provisioning, access control, data ingestion, and processing.

Securing, monitoring, and optimising Amazon MSK

This section focuses on scaling, security, monitoring, and troubleshooting Amazon MSK clusters.

Designing streaming data analytics solutions

The course concludes with reviewing streaming use cases, designing streaming analytics workflows, and exploring modern data architectures on AWS.

Practical information

Duration: 1 day
Price: 9 900 NOK
Course level: Intermediate

FAQ

Er dette et sertifiseringskurs?
Nei, dette er et opplæringskurs og gir ingen formell sertifisering.

Er kurset praktisk rettet?
Ja, kurset inkluderer presentasjoner, praktiske laber, diskusjoner og klasseøvelser.

Hvilke AWS-tjenester jobber man med i kurset?
Kurset dekker blant annet Amazon Kinesis, Amazon MSK, AWS Glue og AWS Lambda.

Passer kurset for deltakere uten erfaring med streaming?
Noe erfaring med data analytics eller sanntidsapplikasjoner anbefales for å få fullt utbytte.

Dekker kurset moderne dataarkitekturer?
Ja, kurset setter streaming analytics inn i konteksten av moderne dataarkitekturer på AWS.

Price:	9,900 NOK
Included items:	Course documentation and exercises. Lunch and refreshments for in class events only.
Hours	09:00 - 17:00
Durance:	1 days
Languages	Norwegian, English