Course Outline
Course Outline: Day 1
• Introduction to data streaming principles
• Fundamentals of batch vs. real-time processing
• Basics of event-driven architecture
• Common industry use cases
• Overview of the streaming ecosystem
Day 2
• Design patterns for streaming architectures
• Fundamentals of distributed messaging systems
• Roles of producers and consumers
• Understanding topics, partitions, and data flow
• Strategies for data ingestion
Day 3
• Concepts and frameworks for stream processing
• Differentiating event-time from processing-time
• Windowing techniques and their applications
• Stateful stream processing
• Fundamentals of fault tolerance and checkpointing
Day 4
• Data transformation within streaming pipelines
• ETL and ELT workflows in real-time systems
• Schema management and evolution
• 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 optimization strategies
• Comprehensive review of end-to-end pipeline design
• Real-world applications, such as 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
