Course Outline
Course Syllabus: Day 1
• Introduction to data streaming principles
• Foundational concepts: Batch vs real time processing
• Basics of event driven architecture
• Typical industry applications
• Overview of the streaming technology ecosystem
Day 2
• Design patterns for streaming architecture
• Core principles of distributed messaging systems
• Roles of producers and consumers
• Topics, partitioning, and data movement
• Strategies for data ingestion
Day 3
• Stream processing principles and frameworks
• Comparison of event time vs processing time
• Windowing methods and practical applications
• Stateful stream processing
• Fundamentals of fault tolerance and checkpointing
Day 4
• Data transformation within streaming pipelines
• ETL and ELT processes in real time environments
• Schema management and evolution
• Stream joins and data enrichment
• Introduction to cloud-based streaming services
Day 5
• Monitoring and observability for streaming systems
• Fundamentals of security and access control
• Performance tuning and optimization techniques
• Comprehensive review of end-to-end pipeline design
• Practical industry applications, 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
