Enable and Detail Data Ingestion Patterns, Including Batch, Streaming, and Incremental Loading, and Import Data from Sources Such as Local Files, Lakeflow Connect Standard Connectors, and Lakeflow Connect Managed Connectors. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A marketing team wants to ingest customer data from Salesforce into Databricks on a daily basis. They need a simple setup without writing custom code. Which approach should they use?

   • AUse Auto Loader to incrementally load Salesforce data from a cloud storage location.
   • BUse a Lakeflow Connect standard connector for Salesforce to schedule a daily batch ingestion.
   • CWrite a custom Python script using the Salesforce REST API and run it as a Databricks job.
   • DManually export Salesforce data to CSV and upload it to Databricks using the UI.
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2. 12foundation · easy

   Which tool can a data engineer use to import a local CSV file into a Databricks table without writing code?

   • AThe Databricks REST API's `POST /api/2.0/workspace/import` endpoint
   • BThe `dbutils.fs.put` command
   • CThe Databricks UI's data import feature
   • DThe Databricks CLI's `databricks fs cp` command
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4. 13foundation · easy

   Which statement best describes a characteristic of batch ingestion?

   • AIt processes data continuously with sub-second latency.
   • BIt only loads data that has changed since the last run.
   • CIt loads data in discrete, scheduled jobs, often at regular intervals.
   • DIt requires a continuous connection to the source system.
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5. 14expert · hard

   A company currently uses a Lakeflow Connect standard connector to ingest data from a cloud database into Databricks on a nightly schedule. The data volume has grown significantly, and the nightly batch now takes longer than the scheduled window allows. The team needs to reduce the load time without changing the batch pattern. Which approach should they take?

   • AUse incremental loading with a watermark column to load only new or changed data since the last run.
   • BSwitch to a Lakeflow Connect managed connector to enable continuous incremental replication.
   • CUse Auto Loader to load the data from the source database in a streaming fashion.
   • DIncrease the cluster size for the nightly job to process the full load faster.
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6. 15foundation · easy

   How does streaming ingestion differ from batch ingestion?

   • AStreaming requires a data warehouse, while batch requires a data lake.
   • BStreaming processes data continuously with low latency, while batch processes data in discrete scheduled jobs.
   • CStreaming loads data once a day, while batch loads data every few seconds.
   • DStreaming is only used for structured data, while batch is used for unstructured data.
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