Configure Lakeflow Connect to Reliably Ingest Data from Diverse Enterprise Sources into UnityCatalog–governed Tables. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which of the following is a factor that can impact the throughput of a Lakeflow Connect ingestion pipeline?

   • AThe color scheme of the Databricks workspace.
   • BThe version of the web browser used to configure the pipeline.
   • CThe number of users viewing the target table.
   • DThe source system's API rate limits.
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2. 2foundation · easy

   When would a full load strategy be more appropriate than an incremental load in Lakeflow Connect?

   • AWhen the source system does not provide any change tracking or timestamp columns.
   • BWhen the target table needs to be updated with only the latest changes.
   • CWhen the source data changes frequently and you need near-real-time updates.
   • DWhen the target table is very large and you want to minimize load time.
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4. 3foundation · easy

   Which of the following is an example of an error handling strategy in Lakeflow Connect?

   • AStopping the entire pipeline when any record fails.
   • BAutomatically deleting the source data after a successful load.
   • CIgnoring all errors and continuing without logging.
   • DSkipping invalid records and logging them for later review.
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5. 4expert · hard

   A data engineer is troubleshooting a Lakeflow Connect pipeline that ingests data from a REST API. The pipeline fails intermittently with HTTP 429 (Too Many Requests) errors. The team needs to ensure the pipeline completes successfully without manual intervention, but they also want to avoid overloading the API. What should be configured?

   • ASet a retry policy with exponential backoff and respect the API's Retry-After header.
   • BSwitch to a full load instead of incremental to reduce the number of requests.
   • CIncrease the request rate to get past the rate limit faster.
   • DDisable retries and rely on the next scheduled run to pick up the data.
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6. 5foundation · easy

   What is the primary purpose of Lakeflow Connect in the Databricks platform?

   • ATo manage access control and lineage for tables already stored in Unity Catalog.
   • BTo serve as a data visualization tool for building dashboards and reports from data stored in Unity Catalog.
   • CTo provide a managed service for ingesting data from various enterprise sources into Unity Catalog-governed tables.
   • DTo provide a serverless compute engine for running ad-hoc SQL queries on external data sources.
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