- Traditionelles vs. Cloud Data Warehousing (Shared Disk und Shared Nothing Architekturen, Vorteile Cloud Computing)
- Hauptakteure Cloud Data Warehousing (AWS Redshift, Azure Synapse Analytics, Google Big Query, Snowflake)
Description
Special focus is placed on the Snowflake Cloud Data Warehouse and AWS-native solutions based on Redshift in combination with other AWS services (e.g. Lambda, Glue, EMR, Lake Formation). Common cloud data warehouse architectures using Redshift and Snowflake are examined in more detail in order to define rough guidelines for use cases for these two data warehouse solutions.
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Experts

Niels Warnecke
Senior Lead Consultant
Agenda
Introduction
Data Storage
- Hot / Cold Storage (AWS S3, AWS Glacier, Snowflake Stages)
- Semi-Structured Data (Snowflake Variant Datentyp)
Data Transformation
- Performance classes (AWS Lambda, AWS EMR, AWS Glue, Snowflake procedures)
- Process automation, orchestration, and monitoring (AWS Lambda, AWS StepFunctions, AWS CloudWatch, Snowflake streams, tasks, and procedures)
Data Analysis
- Integration Cold Data (AWS Redshift Spectrum, AWS Athena, Snowflake External Tables)
- BI-Analyse (3rd Party Tools)
Basic information
Prerequisites
Basic knowledge of cloud mechanisms and Snowflake would be an advantage.
Method
Online-Webinar
Target audience
This webinar is aimed at IT project managers and engineers who are interested in Snowflake or Redshift as a platform.
Languages
German