BenchMark Quizzes by MDFT Pro

Determine If You Can Stream Large Data Sets At Once

You work as a data processing architect for MDFT Pro, a well-known training agency that provides Microsoft certification courses. The company is evaluating different data processing approaches for handling their various analytical needs. They have both real-time requirements like monitoring student engagement during live sessions and batch requirements like generating monthly course completion reports. Mark, the data engineering director, has asked you to explain the limitations and capabilities of stream processing.

Claire, the analytics team lead, needs to understand whether stream processing would be suitable for processing large historical datasets containing years of student enrollment records, course completion data, and assessment results all at once for a comprehensive annual analysis report.

Can you stream a large set of data at once in stream processing?

Choose the correct answer from the options below.

Explanations for each answer:

Yes is incorrect. Stream processing is designed to handle continuous streams of individual records or small batches, not large datasets all at once. Processing large datasets simultaneously would contradict the fundamental principles of streaming and could overwhelm the processing system.
No is correct. Stream processing is architected to handle continuous streams of data records one at a time or in small increments, not large datasets all at once. For processing large historical datasets simultaneously, batch processing is the appropriate approach as it's designed to handle high-volume data processing in scheduled operations.
Only during off-peak hours is incorrect. Stream processing operates continuously regardless of time of day, processing data as it arrives in real-time. The limitation isn't about timing but about the fundamental design principle of processing data incrementally rather than in large batches.
Only with additional memory is incorrect. The limitation isn't hardware-related but conceptual. Stream processing is architected to process data continuously in small increments, which is fundamentally different from batch processing large datasets regardless of available memory.

Learn more about stream processing:

Stream Processing

Exam Preparation Quiz

Determine If You Can Stream Large Data Sets At Once