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Data Ingestion and TransformationeasyMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

A company uses AWS Glue to run ETL jobs that process data from Amazon RDS to Amazon S3. The job runs successfully but the data in S3 is missing some records that exist in the source. The engineer notices that the job uses a JDBC connection and the query extracts data based on a timestamp column. What is the MOST likely cause of the missing records?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

The timestamp column includes time portion and the job is using an exclusive upper bound.

The job extracts data based on a timestamp column and uses an exclusive upper bound (e.g., WHERE timestamp < some_value). If the timestamp includes a time portion, records with a timestamp exactly equal to the upper bound are excluded, causing them to be missing from S3. Option B is incorrect because S3 bucket permissions would cause the job to fail, not simply miss records. Option C is incorrect because connection pooling does not cause records to be dropped. Option D is incorrect because the Glue job can be configured to read from multiple tables; this is unrelated to the missing records.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • The timestamp column includes time portion and the job is using an exclusive upper bound.

    Why this is correct

    Correct. When extracting data using a timestamp column, if the job uses an exclusive upper bound, records with timestamps equal to the boundary value may be missed, especially when the timestamp includes time portion.

  • The S3 bucket lacks write permissions.

    Why it's wrong here

    Incorrect. If the S3 bucket lacked write permissions, the job would fail entirely, not just miss some records.

  • The JDBC connection uses connection pooling, causing some records to be dropped.

    Why it's wrong here

    Incorrect. Connection pooling is a technique to reuse database connections and does not cause records to be dropped.

  • The Glue job is configured to only read from one table.

    Why it's wrong here

    Incorrect. The Glue job can be configured to read from multiple tables; reading from only one table would not cause missing records from the source.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.