+49 (911) 80 10 30

Give us a call or have us call you back!

Simply leave a message with your callback appointment

Your Name *

Your phone number *

Callback date *

Callback time *

Your request *

In order to process your request, it is necessary to process the data you provide. This means that by submitting the contact form, you consent to your data being processed (see Privacy Policy). You can object to the processing of your data at any time.

* All fields marked with an asterisk are mandatory fields.
Send a message

Your Name *

Your email *

Your phone number

Your request *

In order to process your request, it is necessary to process the data you provide. This means that by submitting the contact form, you consent to your data being processed (see Privacy Policy). You can object to the processing of your data at any time.*

* All fields marked with an asterisk are mandatory fields.
Social Media

Share page

AW310: Data Engineering on AWS™ NEW

Training: AWS™ - Cloud

The course provides hands-on knowledge of data engineering solutions with AWS™. Participants learn how to design, implement and secure data solutions – from fundamentals to implementation of data lakes, data warehouses as well as batch and streaming pipelines. The objective is to enable data experts to design modern data architectures efficiently and scalably.

Appointment selection

Appointments in English language (0)


Unfortunately there are currently no available appointments. Would you like to request an appointment? Then click on 'No matching appointment?'

Possible course languages: German

Request prefered appointment period:

Your Name *

Your email *

Your phone number

Preferred period from *

Preferred period to *

Number of participants *

Your message

* All fields marked with an asterisk are mandatory fields.

Unfortunately there are currently no available appointments.
Would you like to request an appointment? Then click on 'No matching appointment?'

Request prefered appointment period:

Your Name *

Your email *

Your phone number

Preferred period from *

Preferred period to *

Number of participants *

Your message

* All fields marked with an asterisk are mandatory fields.

Agenda:

Data Engineering Roles and Key Concepts

The role of a data engineer
Data discovery for a data analytics system
AWS™ services for data workflows
Continuous integration and continuous delivery
Networking considerations

Designing and Implementing Data Lakes

Data lake introduction
Data lake storage
Ingest data
Catalog data
Transform data
Serve data for consumption
Hands-on Lab: Setting up a Data Lake on AWS™

Optimizing and Securing Data Lake Solutions

Optimizing performance
Security using Lake Formation
Setting permissions with Lake Formation
Security and governance
Troubleshooting
Hands-on Lab: Develop Retrieval Augmented Generation (RAG) Applications with Amazon
Bedrock Knowledge Bases

Data Warehouse Architecture and Design Principles

Introduction to data warehouses
Amazon Redshift overview
Ingesting data into Amazon Redshift
Processing data
Serving data for consumption
Hands-on Lab: Setting up a Data Warehouse using Amazon Redshift Serverless

Performance Optimization Techniques for Data Warehouses

Monitoring and optimization options
Data optimization in Amazon Redshift
Query optimization in Amazon Redshift
Data orchestration

Security and Access Control for Data Warehouses

Authentication and access control in Amazon Redshift
Data security in Amazon Redshift
Hands-on Lab: Working with Amazon Redshift

Designing Batch Data Pipelines

Introduction to batch data pipelines
Designing a batch data pipeline
Ingesting batch data

Implementing Strategies for Batch Data Pipelines

Processing and transforming data
Transforming data formats
Integrating your data
Cataloging data
Serving data for consumption
Hands-on Lab: A Day in the Life of a Data Engineer

Optimizing, Orchestrating, and Securing Batch Data Pipelines

Optimizing the batch data pipeline
Orchestrating the batch data pipeline
Securing the batch data pipeline
Hands-on Lab: Orchestrating Data Processing in Spark using AWS™ Step Functions

Streaming Data Architecture Patterns

Introduction to streaming data pipelines
Ingesting data from stream sources
Storing streaming data
Processing streaming data
Analyzing streaming data
Hands-on Lab: Streaming Analytics with Amazon Managed Service for Apache Flink

Optimizing and Securing Streaming Solutions

Optimizing a streaming data solution
Securing a streaming data pipeline
Hands-on Lab: Access Control with Amazon Managed Streaming for Apache Kafka

Compliance and Cost Optimization

Compliance considerations
Cost optimization tools

Course Wrap-Up

Objectives:

In the course AW310 AData Engineering on AWS™, you will learn to do the following:

Design and implement scalable data lakes and data warehouses on AWS™
Build, optimize, and secure batch data processing pipelines
Develop and manage streaming data solutions
Apply best practices for data governance and security
Automate data engineering workflows by using AWS™ services
Implement access control and security measures for data solutions

Target audience:

This course AW310 Data Engineering on AWS™ is is targeted at:

Data engineers
Solutions architects
DevOps engineers
IT professionals
Data analysts looking to expand into data engineering

Prerequisites:

To participate in the course AW310 Data Engineering on AWS™ at qSkills™, we recommend that attendees have the following:

Basic understanding of AWS™ services
Familiarity with database concepts
Basic programming or scripting knowledge
Understanding of data processing fundamentals

Description:

This comprehensive 3-day instructor-led training provides a deep dive into data engineering practices and
solutions on Amazon Web Services (AWS™). Participants of the course AW310 Data Engineering on AWS™ will learn how to design, build, optimize, and secure data engineering solutions by using AWS™ services. Topics range from foundational concepts to hands-on implementation of data lakes, data warehouses, and both batch and streaming data pipelines.
This course equips data professionals with the skills needed to architect and manage modern data
solutions at scale.