Databricks Updated Databricks-Certified-Data-Engineer-Associate Exam Questions and Answers by ema

Structured Streaming provides native Kafka integration and processes incoming records in repeated micro-batches, making it suitable for the required sub-minute clickstream latency. For the customer data, an incremental Lakeflow Connect ingestion pattern tracks source progress and processes only new or changed records during subsequent executions. This avoids repeatedly transferring and processing unchanged Snowflake rows. Option B performs a complete extraction every four hours, so the later MERGE does not eliminate unnecessary source reading and network transfer. Option C relies on a time filter that may miss late changes, updates without a suitable timestamp, or records affected by clock boundaries. Option D explicitly performs full refreshes and therefore violates the requirement to prevent reprocessing unchanged customer data. Consequently, option A is the only approach that satisfies both the streaming-latency and incremental-ingestion requirements.

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According to the medallion lakehouse architecture, gold tables are the final layer of data that powers analytics, machine learning, and production applications. They are often highly refined and aggregated, containing data that has been transformed into knowledge, rather than just information. Silver tables, on the other hand, are the intermediate layer of data that represents a validated, enriched version of the raw data from the bronze layer. They provide an enterprise view of all its key business entities, concepts and transactions, but they may not have all the aggregations and calculations that are required for specific use cases. Therefore, gold tables are more likely to contain aggregations than silver tables. References:

What is the medallion lakehouse architecture?

What is a Medallion Architecture?