Data Acquisition GMLE Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A data engineering team is designing an ingestion pipeline that reads CSV files from an SFTP server, validates the schema, and loads the data into a data warehouse. The pipeline must be able to re-run without duplicating records if a file is processed twice. Which design feature is essential?

   • AA notification system that alerts the team when a file is processed.
   • BA high-performance parallel load that reads all files simultaneously.
   • CA schema validation step that fails the pipeline on any unexpected column.
   • DIdempotent writes that use a unique key or load manifest to skip already-processed files.
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2. 12expert · hard

   A machine learning team is working on a project that requires regulatory compliance. They must be able to prove which data was used to train each model. The data is stored in a data lake and updated weekly. What should they implement?

   • AA policy to delete old data after model training
   • BA data catalog that records dataset versions, hashes, and model associations
   • CA manual spreadsheet of model training runs
   • DA simple folder structure with dates in the names
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4. 13foundation · easy

   When extracting data from a REST API, which HTTP method is typically used to retrieve data?

   • ADELETE
   • BGET
   • CPOST
   • DPUT
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5. 14application · medium

   During ingestion of a new data feed, a data engineer notices that some records have missing timestamps and others have timestamps in different time zones. The downstream model requires a consistent UTC timestamp for every record. What should the engineer do first?

   • AImplement a validation step in the ingestion pipeline that flags records with missing or ambiguous timestamps and applies a documented timezone conversion policy.
   • BLoad the data as-is and let the model handle missing or inconsistent timestamps.
   • CDrop all records with missing or inconsistent timestamps before loading.
   • DConvert all timestamps to UTC using the server's local timezone as the default.
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6. 15application · medium

   A data analyst is acquiring data from a partner via a CSV file. The analyst notices that some rows have extra commas, causing the file to be parsed incorrectly. What should the analyst do to ensure accurate data acquisition?

   • AIgnore the rows with extra commas
   • BManually edit the CSV file to remove extra commas
   • CUse a simple split on commas and hope for the best
   • DUse a CSV parser that handles quoted fields and validate the row structure
   Reveal Solution Discussion Select an answer first