Microsoft Certified: Fabric Analytics Engineer AssociatePlan and implement data analytics solutions (10-15%)Hard
A company is ingesting real-time financial transaction data into a Microsoft Fabric Lakehouse. The data arrives at a high velocity (thousands of events per second) and needs to be available for near real-time analytics. To handle this volume efficiently and ensure consistent data quality, the data engineering team wants to aggregate these events into small, manageable batches before writing them to the Lakehouse. Which ingestion pattern is being described?
- AFull data replication.
- BBatch processing.
- CMicro-batching.
- DStream processing.
Show answer & explanationAnswer & explanation
Correct answer: C. Micro-batching.
Micro-batching is an ingestion pattern that processes real-time data by collecting small batches of records over very short intervals (e.g., seconds) and then processing each batch as a unit. This provides a balance between true stream processing and traditional batch processing, suitable for high-velocity data needing near real-time analytics.
Why the other options are wrong
- A. Full data replication is a strategy for copying entire datasets, not an ingestion pattern for high-velocity streaming data.
- B. Batch processing typically involves larger data volumes and longer processing intervals, not suitable for near real-time.
- D. True stream processing processes individual events as they arrive, which can be more complex to manage for transactional guarantees and may not be necessary if 'near real-time' is acceptable.
Micro-batching
Micro-batching is a data processing technique where continuous streams of data are broken down into small, time-based batches, which are then processed as traditional batches, providing near real-time analytics capabilities.
- Balances latency and throughput for streaming data.
- Processes data in small, frequent intervals (e.g., seconds).
- Often used in Spark Streaming or similar frameworks.
Memory trick: Small batches, fast insights, micro-batching ignites!