Data Engineering on Cloud Platforms

Course overview

The course provides the fundamentals and application areas of Data Engineering on cloud platforms. Topics include cloud data platforms (Data Lake, Data Warehouse, Lakehouse), SQL for analytics, data ingestion from batch, streaming, and change data capture sources, data processing with distributed methods, ETL and ELT processes, streaming processing and distributed clusters, data modeling (normalization, dimensional modeling, partitioning strategies), data storage and storage strategies (object storage, cloud data warehouse, column formats), data quality and validation, data lifecycle and cataloging, pipeline operation with orchestration and monitoring, as well as security and data governance. The course concludes with a practical project focused on an end-to-end data pipeline. In the practical project, a complete pipeline is created, encompassing ingestion, transformation, modeling, quality assurance, orchestration, and monitored delivery. Cloud data platforms Data Lake, Data Warehouse, and Lakehouse Data ingestion from various sources Data processing and ETL/ELT Distributed cluster and stream processing Data modeling: normalization and dimensional modeling Data storage and storage strategies Data quality and validation Data lifecycle, cataloging, and cost management Pipeline operation, orchestration, and monitoring Security and data governance on cloud platforms

Upcoming dates

• 2027-04-25T22:00:00.000Z · 2027-07-15T22:00:00.000Z · Saarbrücken · Combined Learning
• 2027-04-25T22:00:00.000Z · 2027-07-15T22:00:00.000Z · Landshut, Isar · Combined Learning
• 2027-04-25T22:00:00.000Z · 2027-07-15T22:00:00.000Z · Stade, Niederelbe · Combined Learning
• 2027-04-25T22:00:00.000Z · 2027-07-15T22:00:00.000Z · Montabaur · Combined Learning
• 2027-04-25T22:00:00.000Z · 2027-07-15T22:00:00.000Z · Stadthagen · Combined Learning