Course Outline
Course Outline: Day 1
• Introduction to data streaming principles
• Fundamentals comparing batch and real-time processing
• Basics of event-driven architecture
• Common industry applications
• Overview of the streaming technology ecosystem
Day 2
• Design patterns for streaming architecture
• Fundamentals of distributed messaging systems
• Roles of producers and consumers
• Understanding topics, partitions, and data flow
• Strategies for data ingestion
Day 3
• Stream processing principles and available frameworks
• Differences between event time and processing time
• Windowing techniques and their applications
• Stateful stream processing mechanisms
• Introduction to fault tolerance and checkpointing
Day 4
• Data transformation within streaming pipelines
• ETL and ELT practices in real-time systems
• Schema management and evolution strategies
• Stream joins and data enrichment
• Introduction to cloud-based streaming services
Day 5
• Monitoring and observability in streaming environments
• Basics of security and access control
• Performance tuning and optimisation
• Review of end-to-end pipeline design
• Real-world case studies, including fraud detection and IoT processing
Testimonials (2)
A journey through the Spark world: a very intense course. DSL, spark sql, partitioning vs bucketing for me.
Georgiana Elisabeta
Course - Apache Spark Fundamentals
Hands on exercises. Class should have been 5 days, but the 3 days helped to clear up a lot of questions that I had from working with NiFi already
