Data Ingestion DY0-001 Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   Which characteristic best describes streaming data ingestion?

   • AData is processed in small, continuous increments as it arrives
   • BData is collected and processed in large, scheduled batches
   • CData is only processed after a manual trigger
   • DData is stored indefinitely before any processing occurs
   Reveal Solution Discussion Select an answer first
2. 22expert · hard

   A data platform team is migrating from a monolithic ETL tool to a modern pipeline. The team must ensure that if a pipeline step fails, the error can be traced to the exact source record and transformation. The team also needs to support re-processing of failed records without affecting already-processed data. Which two features are most critical to implement?

   • AData compression and encryption
   • BData lineage tracking and idempotent writes
   • CData masking and data validation
   • DData partitioning and data compression
   Reveal Solution Discussion Select an answer first
4. 23expert · hard

   A manufacturing company collects sensor data from its production line. The company needs to monitor equipment health in near-real-time to prevent failures, but it also needs to generate detailed daily production reports. The sensor data is high-frequency and must be stored for long-term analysis. Which ingestion strategy best meets these needs?

   • AStreaming ingestion for real-time monitoring and batch ingestion for daily reports and long-term storage
   • BBatch ingestion for both real-time monitoring and daily reports
   • CMicro-batch ingestion every 5 minutes for both use cases
   • DStreaming ingestion for both real-time monitoring and daily reports
   Reveal Solution Discussion Select an answer first
5. 24expert · hard

   A streaming platform ingests millions of events per second from IoT devices. The platform must process these events with minimal latency, but the downstream analytics system can only handle a limited number of writes per second. The engineering team needs to reduce the write load without losing important event details. Which approach is most effective?

   • AWriting every event directly to the analytics system
   • BAggregating events in the stream before writing to the analytics system
   • CDropping events that are not considered important
   • DUsing a batch job to process events every hour
   Reveal Solution Discussion Select an answer first
6. 25application · medium

   A retail company collects point-of-sale transactions from 200 stores. Each night, the corporate office runs a job that extracts the day's transactions from each store's local database, transforms them into a unified format, and loads them into a central data warehouse for morning reporting. The stores' databases are only accessible during off-hours, and the reporting team needs the data available by 6:00 AM. Which data ingestion approach best fits this requirement?

   • ABatch processing with an ETL pipeline scheduled for off-hours
   • BChange data capture (CDC) with continuous replication to the warehouse
   • CManual file transfer of CSV exports from each store each morning
   • DStreaming ingestion with a message broker such as Apache Kafka
   Reveal Solution Discussion Select an answer first