Fabric Eventstreams Real-Time Ingestion Quiz

1. What is the function of a 'union' node in Eventstreams?

Merge multiple event streams into a single stream

Split one stream into several outputs

Remove duplicate events

Convert event format to JSON

2. Which of these is NOT a typical use case for Fabric Eventstreams?

Real-time fraud detection

IoT sensor data collection

Static annual financial reporting

Live dashboard updates from events

3. In Eventstreams, what does 'exactly-once' delivery guarantee mean?

Each event is processed exactly one time without duplication or loss

Events are delivered only once per day

Only one destination can receive the event

The first event is always processed first

4. True or False: You can apply multiple transformations to a single event before routing it to a destination.

True

False

5. Which monitoring feature helps track Eventstream performance?

Event count and throughput metrics

Latency and failure rate dashboards

Data quality and schema validation reports

All of the above

6. What type of processing does Eventstreams primarily support?

Batch processing only

Stream processing only

Both batch and stream processing

Neither; it only stores data

7. True or False: Eventstreams can directly consume data from Azure Synapse pipelines.

True

False

8. In Eventstreams, what is 'event enrichment'?

Adding metadata or context from external sources to events

Removing unnecessary fields from events

Encrypting sensitive event data

Grouping events by timestamp

9. Which Fabric component is best suited for storing the output of an Eventstream for analytical queries?

Lakehouse

Data Warehouse

KQL Database

All are equally suitable

10. True or False: Eventstreams requires you to manually manage scaling and throughput limits.

True

False

11. What is the primary purpose of Microsoft Fabric Eventstreams in data engineering?

Store historical data for batch processing

Ingest, process, and route real-time event data

Create static data warehouses

Manage user authentication and security

12. Which of these scenarios best fits Eventstreams architecture?

Batch processing historical data monthly

Real-time monitoring of IoT sensor data

Static reporting on archived logs

One-time data migration

13. True or False: Eventstreams automatically handles schema evolution for incoming events.

True

False

14. In Eventstreams, what does 'fan-out' refer to?

Splitting a single stream into multiple output paths

Combining multiple streams into one

Delaying event processing

Reducing event payload size

15. Which transformation node allows you to enrich events with external data?

Aggregate

Lookup

Funnel

Union

16. True or False: Eventstreams can process events with sub-second latency.

True

False

17. What is the role of a 'filter' node in an Eventstream?

Aggregate multiple event streams

Select only events matching specified conditions

Encrypt sensitive data fields

Batch events into fixed-size groups

18. Which destination can you route Eventstreams data to for real-time analytics?

Fabric Data Warehouse

Fabric KQL Database

Lakehouse

All of the above

19. In Eventstreams, what does a 'node' represent?

A storage container for data

A processing unit that transforms or routes events

A user account with permissions

A backup replica of the data

20. Which of the following is a supported event source in Fabric Eventstreams?

Azure Event Hubs

Kafka topics

IoT Hub

All of the above

Fabric Data Engineer Eventstreams Real Time Ingestion Quiz

1. What is the function of a 'union' node in Eventstreams?

2.

What first name or nickname would you like us to use?

2. Which of these is NOT a typical use case for Fabric Eventstreams?

3. In Eventstreams, what does 'exactly-once' delivery guarantee mean?

4. True or False: You can apply multiple transformations to a single event before routing it to a destination.

5. Which monitoring feature helps track Eventstream performance?

6. What type of processing does Eventstreams primarily support?

7. True or False: Eventstreams can directly consume data from Azure Synapse pipelines.

8. In Eventstreams, what is 'event enrichment'?

9. Which Fabric component is best suited for storing the output of an Eventstream for analytical queries?

10. True or False: Eventstreams requires you to manually manage scaling and throughput limits.

11. What is the primary purpose of Microsoft Fabric Eventstreams in data engineering?

12. Which of these scenarios best fits Eventstreams architecture?

13. True or False: Eventstreams automatically handles schema evolution for incoming events.

14. In Eventstreams, what does 'fan-out' refer to?

15. Which transformation node allows you to enrich events with external data?

16. True or False: Eventstreams can process events with sub-second latency.

17. What is the role of a 'filter' node in an Eventstream?

18. Which destination can you route Eventstreams data to for real-time analytics?

19. In Eventstreams, what does a 'node' represent?

20. Which of the following is a supported event source in Fabric Eventstreams?