Databricks Certified Data Engineer - Professional

Explanation

In stream processing, datasets are continuous and unbounded.

Key Concepts:

• Continuous: Data arrives continuously in real-time, without predefined start or end points
• Unbounded: There is no fixed size or limit to the data stream - it can theoretically continue indefinitely

Why Other Options Are Incorrect:

• A. continuous and bounded: While stream data is continuous, it's not bounded (limited in size)
• C. micro-batch and unbounded: Micro-batch processing is a specific implementation approach, not a characteristic of the dataset itself
• D. micro-batch and bounded: This describes batch processing characteristics, not stream processing

Stream Processing Characteristics:

• Real-time data ingestion
• No predefined dataset boundaries
• Processing occurs as data arrives
• Suitable for scenarios requiring immediate insights and actions

This distinguishes stream processing from batch processing, where datasets are discrete and bounded.