Data ETL Advanced MCQ Questions with Answers – Page 2 (Latest 2026)

Q51. Which statement about vacuuming is most accurate?

A. A pure index rebuild. B. A pure schema change. C. A pure backup. D. Remove old/unused data files (with retention).

Select an answer to check.

Answer: Remove old/unused data files (with retention).

Here, Remove old/unused data files (with retention). is the right choice. Required for cost control. It aligns directly with what the question asks about which statement about vacuuming is most accurate. Competing choices sound plausible, but they miss the key condition.

Q52. How is vacuuming best characterized?

A. A pure backup. B. A pure index rebuild. C. Remove old/unused data files (with retention). D. A pure schema change.

Select an answer to check.

Answer: Remove old/unused data files (with retention).

In this case, Remove old/unused data files (with retention). is correct. Required for cost control. It aligns directly with what the question asks about how is vacuuming best characterized. Competing choices sound plausible, but they miss the key condition.

Q53. Which option best describes time travel?

A. Pure rollback only. B. Pure query log. C. Query data at a past version. D. A pure snapshot index.

Select an answer to check.

Answer: Query data at a past version.

The best option here is Query data at a past version.. Lakehouse feature. It aligns directly with what the question asks about which option best describes time travel. Competing choices sound plausible, but they miss the key condition.

Q54. What is the primary purpose of time travel?

A. Pure rollback only. B. Query data at a past version. C. A pure snapshot index. D. Pure query log.

Select an answer to check.

Answer: Query data at a past version.

For this question, Query data at a past version. is correct. Lakehouse feature. It aligns directly with what the question asks about what is the primary purpose of time travel. Competing choices sound plausible, but they miss the key condition.

Q55. Which statement about time travel is most accurate?

A. A pure snapshot index. B. Pure query log. C. Query data at a past version. D. Pure rollback only.

Select an answer to check.

Answer: Query data at a past version.

Query data at a past version. is the correct answer here. Lakehouse feature. It aligns directly with what the question asks about which statement about time travel is most accurate. Competing choices sound plausible, but they miss the key condition.

Q56. How is time travel best characterized?

A. A pure snapshot index. B. Query data at a past version. C. Pure query log. D. Pure rollback only.

Select an answer to check.

Answer: Query data at a past version.

Here, Query data at a past version. is the right choice. Lakehouse feature. This matches the core idea being tested around how is time travel best characterized. Competing choices sound plausible, but they miss the key condition.

Q57. Which option best describes CDC merge in lake?

A. Pure append only. B. Pure full reload. C. Pure overwrite. D. Apply CDC events into lake table.

Select an answer to check.

Answer: Apply CDC events into lake table.

In this case, Apply CDC events into lake table. is correct. MERGE INTO + watermark. This matches the core idea being tested around which option best describes cdc merge in lake. Competing choices sound plausible, but they miss the key condition.

Q58. What is the primary purpose of CDC merge in lake?

A. Pure overwrite. B. Pure append only. C. Apply CDC events into lake table. D. Pure full reload.

Select an answer to check.

Answer: Apply CDC events into lake table.

The best option here is Apply CDC events into lake table.. MERGE INTO + watermark. This matches the core idea being tested around what is the primary purpose of cdc merge. Competing choices sound plausible, but they miss the key condition.

Q59. Which statement about CDC merge in lake is most accurate?

A. Apply CDC events into lake table. B. Pure append only. C. Pure full reload. D. Pure overwrite.

Select an answer to check.

Answer: Apply CDC events into lake table.

For this question, Apply CDC events into lake table. is correct. MERGE INTO + watermark. This matches the core idea being tested around which statement about cdc merge in lake is. Competing choices sound plausible, but they miss the key condition.

Q60. How is CDC merge in lake best characterized?

A. Pure overwrite. B. Pure append only. C. Pure full reload. D. Apply CDC events into lake table.

Select an answer to check.

Answer: Apply CDC events into lake table.

Apply CDC events into lake table. is the correct answer here. MERGE INTO + watermark. This matches the core idea being tested around how is cdc merge in lake best characterized. Competing choices sound plausible, but they miss the key condition.

Q61. Which option best describes upsert?

A. INSERT only. B. DELETE only. C. Insert if absent, update if present. D. UPDATE only.

Select an answer to check.

Answer: Insert if absent, update if present.

Here, Insert if absent, update if present. is the right choice. Common in CDC pipelines. That is exactly the concept behind which option best describes upsert in this context. Competing choices sound plausible, but they miss the key condition.

Q62. What is the primary purpose of upsert?

A. UPDATE only. B. INSERT only. C. Insert if absent, update if present. D. DELETE only.

Select an answer to check.

Answer: Insert if absent, update if present.

In this case, Insert if absent, update if present. is correct. Common in CDC pipelines. That is exactly the concept behind what is the primary purpose of upsert in this context. Competing choices sound plausible, but they miss the key condition.

Q63. Which statement about upsert is most accurate?

A. INSERT only. B. Insert if absent, update if present. C. UPDATE only. D. DELETE only.

Select an answer to check.

Answer: Insert if absent, update if present.

The best option here is Insert if absent, update if present.. Common in CDC pipelines. That is exactly the concept behind which statement about upsert is most accurate in this context. Competing choices sound plausible, but they miss the key condition.

Q64. How is upsert best characterized?

A. UPDATE only. B. DELETE only. C. Insert if absent, update if present. D. INSERT only.

Select an answer to check.

Answer: Insert if absent, update if present.

For this question, Insert if absent, update if present. is correct. Common in CDC pipelines. That is exactly the concept behind how is upsert best characterized in this context. Competing choices sound plausible, but they miss the key condition.

Q65. Which option best describes type 2 SCD?

A. Type 4 history table only. B. Type 1 overwrite. C. Add new row per attribute change with effective dates. D. Type 0 fixed.

Select an answer to check.

Answer: Add new row per attribute change with effective dates.

Add new row per attribute change with effective dates. is the correct answer here. Preserves history. That is exactly the concept behind which option best describes type 2 scd in this context. Competing choices sound plausible, but they miss the key condition.

Q66. What is the primary purpose of type 2 SCD?

A. Type 4 history table only. B. Add new row per attribute change with effective dates. C. Type 1 overwrite. D. Type 0 fixed.

Select an answer to check.

Answer: Add new row per attribute change with effective dates.

Here, Add new row per attribute change with effective dates. is the right choice. Preserves history. It fits the requirement in the prompt about what is the primary purpose of type 2. Competing choices sound plausible, but they miss the key condition.

Q67. Which statement about type 2 SCD is most accurate?

A. Type 4 history table only. B. Type 0 fixed. C. Type 1 overwrite. D. Add new row per attribute change with effective dates.

Select an answer to check.

Answer: Add new row per attribute change with effective dates.

In this case, Add new row per attribute change with effective dates. is correct. Preserves history. It fits the requirement in the prompt about which statement about type 2 scd is most. Competing choices sound plausible, but they miss the key condition.

Q68. How is type 2 SCD best characterized?

A. Type 4 history table only. B. Add new row per attribute change with effective dates. C. Type 1 overwrite. D. Type 0 fixed.

Select an answer to check.

Answer: Add new row per attribute change with effective dates.

The best option here is Add new row per attribute change with effective dates.. Preserves history. It fits the requirement in the prompt about how is type 2 scd best characterized. Competing choices sound plausible, but they miss the key condition.

Q69. Which option best describes incremental processing watermark?

A. A schema flag. B. A retry counter. C. Earliest unprocessed event time. D. A row count.

Select an answer to check.

Answer: Earliest unprocessed event time.

For this question, Earliest unprocessed event time. is correct. Drives correctness in streams. It fits the requirement in the prompt about which option best describes incremental processing watermark. Competing choices sound plausible, but they miss the key condition.

Q70. What is the primary purpose of incremental processing watermark?

A. A retry counter. B. A schema flag. C. Earliest unprocessed event time. D. A row count.

Select an answer to check.

Answer: Earliest unprocessed event time.

Earliest unprocessed event time. is the correct answer here. Drives correctness in streams. It fits the requirement in the prompt about what is the primary purpose of incremental processing. Competing choices sound plausible, but they miss the key condition.

Q71. Which statement about incremental processing watermark is most accurate?

A. A row count. B. Earliest unprocessed event time. C. A schema flag. D. A retry counter.

Select an answer to check.

Answer: Earliest unprocessed event time.

Here, Earliest unprocessed event time. is the right choice. Drives correctness in streams. This is the most accurate statement for which statement about incremental processing watermark is most. Competing choices sound plausible, but they miss the key condition.

Q72. How is incremental processing watermark best characterized?

A. A retry counter. B. A row count. C. A schema flag. D. Earliest unprocessed event time.

Select an answer to check.

Answer: Earliest unprocessed event time.

In this case, Earliest unprocessed event time. is correct. Drives correctness in streams. This is the most accurate statement for how is incremental processing watermark best characterized. Competing choices sound plausible, but they miss the key condition.

Q73. Which option best describes dead-letter queue?

A. Holds events that couldn't be processed. B. A pure backup. C. A pure index. D. A pure cache.

Select an answer to check.

Answer: Holds events that couldn't be processed.

The best option here is Holds events that couldn't be processed.. Operability mechanism. This is the most accurate statement for which option best describes dead-letter queue. Competing choices sound plausible, but they miss the key condition.

Q74. What is the primary purpose of dead-letter queue?

A. A pure backup. B. A pure cache. C. Holds events that couldn't be processed. D. A pure index.

Select an answer to check.

Answer: Holds events that couldn't be processed.

For this question, Holds events that couldn't be processed. is correct. Operability mechanism. This is the most accurate statement for what is the primary purpose of dead-letter queue. Competing choices sound plausible, but they miss the key condition.

Q75. Which statement about dead-letter queue is most accurate?

A. A pure cache. B. A pure backup. C. A pure index. D. Holds events that couldn't be processed.

Select an answer to check.

Answer: Holds events that couldn't be processed.

Holds events that couldn't be processed. is the correct answer here. Operability mechanism. This is the most accurate statement for which statement about dead-letter queue is most accurate. Competing choices sound plausible, but they miss the key condition.

Q76. How is dead-letter queue best characterized?

A. A pure index. B. Holds events that couldn't be processed. C. A pure cache. D. A pure backup.

Select an answer to check.

Answer: Holds events that couldn't be processed.

Here, Holds events that couldn't be processed. is the right choice. Operability mechanism. It aligns directly with what the question asks about how is dead-letter queue best characterized. The remaining choices fail because they don’t satisfy the full definition.

Q77. Which option best describes backfilling?

A. Reprocess historical data through pipeline. B. Pure full reload only. C. Live processing only. D. Pure schema change.

Select an answer to check.

Answer: Reprocess historical data through pipeline.

In this case, Reprocess historical data through pipeline. is correct. Useful after fixes. It aligns directly with what the question asks about which option best describes backfilling. The remaining choices fail because they don’t satisfy the full definition.

Q78. What is the primary purpose of backfilling?

A. Live processing only. B. Pure schema change. C. Pure full reload only. D. Reprocess historical data through pipeline.

Select an answer to check.

Answer: Reprocess historical data through pipeline.

The best option here is Reprocess historical data through pipeline.. Useful after fixes. It aligns directly with what the question asks about what is the primary purpose of backfilling. The remaining choices fail because they don’t satisfy the full definition.

Q79. Which statement about backfilling is most accurate?

A. Pure full reload only. B. Pure schema change. C. Live processing only. D. Reprocess historical data through pipeline.

Select an answer to check.

Answer: Reprocess historical data through pipeline.

For this question, Reprocess historical data through pipeline. is correct. Useful after fixes. It aligns directly with what the question asks about which statement about backfilling is most accurate. The remaining choices fail because they don’t satisfy the full definition.

Q80. How is backfilling best characterized?

A. Pure full reload only. B. Reprocess historical data through pipeline. C. Pure schema change. D. Live processing only.

Select an answer to check.

Answer: Reprocess historical data through pipeline.

Reprocess historical data through pipeline. is the correct answer here. Useful after fixes. It aligns directly with what the question asks about how is backfilling best characterized. The remaining choices fail because they don’t satisfy the full definition.

Q81. Which option best describes reprocessing?

A. A pure backup. B. Run pipeline again over a range. C. A pure schema migration. D. A pure delete.

Select an answer to check.

Answer: Run pipeline again over a range.

Here, Run pipeline again over a range. is the right choice. Idempotency makes safe. This matches the core idea being tested around which option best describes reprocessing. The remaining choices fail because they don’t satisfy the full definition.

Q82. What is the primary purpose of reprocessing?

A. A pure schema migration. B. A pure delete. C. Run pipeline again over a range. D. A pure backup.

Select an answer to check.

Answer: Run pipeline again over a range.

In this case, Run pipeline again over a range. is correct. Idempotency makes safe. This matches the core idea being tested around what is the primary purpose of reprocessing. The remaining choices fail because they don’t satisfy the full definition.

Q83. Which statement about reprocessing is most accurate?

A. A pure schema migration. B. A pure backup. C. Run pipeline again over a range. D. A pure delete.

Select an answer to check.

Answer: Run pipeline again over a range.

The best option here is Run pipeline again over a range.. Idempotency makes safe. This matches the core idea being tested around which statement about reprocessing is most accurate. The remaining choices fail because they don’t satisfy the full definition.

Q84. How is reprocessing best characterized?

A. Run pipeline again over a range. B. A pure backup. C. A pure schema migration. D. A pure delete.

Select an answer to check.

Answer: Run pipeline again over a range.

For this question, Run pipeline again over a range. is correct. Idempotency makes safe. This matches the core idea being tested around how is reprocessing best characterized. The remaining choices fail because they don’t satisfy the full definition.

Q85. Which option best describes data lineage?

A. Pure logging only. B. Pure caching only. C. Tracking transformations from source to target. D. Pure indexing only.

Select an answer to check.

Answer: Tracking transformations from source to target.

Tracking transformations from source to target. is the correct answer here. Aids governance and debugging. This matches the core idea being tested around which option best describes data lineage. The remaining choices fail because they don’t satisfy the full definition.

Q86. What is the primary purpose of data lineage?

A. Pure logging only. B. Pure caching only. C. Tracking transformations from source to target. D. Pure indexing only.

Select an answer to check.

Answer: Tracking transformations from source to target.

Here, Tracking transformations from source to target. is the right choice. Aids governance and debugging. That is exactly the concept behind what is the primary purpose of data lineage in this context. The remaining choices fail because they don’t satisfy the full definition.

Q87. Which statement about data lineage is most accurate?

A. Pure indexing only. B. Pure logging only. C. Tracking transformations from source to target. D. Pure caching only.

Select an answer to check.

Answer: Tracking transformations from source to target.

In this case, Tracking transformations from source to target. is correct. Aids governance and debugging. That is exactly the concept behind which statement about data lineage is most accurate in this context. The remaining choices fail because they don’t satisfy the full definition.

Q88. How is data lineage best characterized?

A. Tracking transformations from source to target. B. Pure caching only. C. Pure logging only. D. Pure indexing only.

Select an answer to check.

Answer: Tracking transformations from source to target.

The best option here is Tracking transformations from source to target.. Aids governance and debugging. That is exactly the concept behind how is data lineage best characterized in this context. The remaining choices fail because they don’t satisfy the full definition.

Q89. Which option best describes data contracts?

A. Producer-consumer schema/SLA agreements. B. No agreements. C. Free-form schemas. D. Pure manual emails.

Select an answer to check.

Answer: Producer-consumer schema/SLA agreements.

For this question, Producer-consumer schema/SLA agreements. is correct. Stable interfaces between teams. That is exactly the concept behind which option best describes data contracts in this context. The remaining choices fail because they don’t satisfy the full definition.

Q90. What is the primary purpose of data contracts?

A. Pure manual emails. B. Free-form schemas. C. Producer-consumer schema/SLA agreements. D. No agreements.

Select an answer to check.

Answer: Producer-consumer schema/SLA agreements.

Producer-consumer schema/SLA agreements. is the correct answer here. Stable interfaces between teams. That is exactly the concept behind what is the primary purpose of data contracts in this context. The remaining choices fail because they don’t satisfy the full definition.

Q91. Which statement about data contracts is most accurate?

A. Pure manual emails. B. Free-form schemas. C. Producer-consumer schema/SLA agreements. D. No agreements.

Select an answer to check.

Answer: Producer-consumer schema/SLA agreements.

Here, Producer-consumer schema/SLA agreements. is the right choice. Stable interfaces between teams. It fits the requirement in the prompt about which statement about data contracts is most accurate. The remaining choices fail because they don’t satisfy the full definition.

Q92. How is data contracts best characterized?

A. Producer-consumer schema/SLA agreements. B. No agreements. C. Pure manual emails. D. Free-form schemas.

Select an answer to check.

Answer: Producer-consumer schema/SLA agreements.

In this case, Producer-consumer schema/SLA agreements. is correct. Stable interfaces between teams. It fits the requirement in the prompt about how is data contracts best characterized. The remaining choices fail because they don’t satisfy the full definition.

Q93. Which option best describes data observability?

A. Pure SLA only. B. Pure CPU/memory only. C. Freshness, volume, schema, distribution monitoring. D. Pure pipeline logs only.

Select an answer to check.

Answer: Freshness, volume, schema, distribution monitoring.

The best option here is Freshness, volume, schema, distribution monitoring.. Detects issues fast. It fits the requirement in the prompt about which option best describes data observability. The remaining choices fail because they don’t satisfy the full definition.

Q94. What is the primary purpose of data observability?

A. Pure SLA only. B. Freshness, volume, schema, distribution monitoring. C. Pure CPU/memory only. D. Pure pipeline logs only.

Select an answer to check.

Answer: Freshness, volume, schema, distribution monitoring.

For this question, Freshness, volume, schema, distribution monitoring. is correct. Detects issues fast. It fits the requirement in the prompt about what is the primary purpose of data observability. The remaining choices fail because they don’t satisfy the full definition.

Q95. Which statement about data observability is most accurate?

A. Pure pipeline logs only. B. Freshness, volume, schema, distribution monitoring. C. Pure CPU/memory only. D. Pure SLA only.

Select an answer to check.

Answer: Freshness, volume, schema, distribution monitoring.

Freshness, volume, schema, distribution monitoring. is the correct answer here. Detects issues fast. It fits the requirement in the prompt about which statement about data observability is most accurate. The remaining choices fail because they don’t satisfy the full definition.

Q96. How is data observability best characterized?

A. Pure pipeline logs only. B. Pure CPU/memory only. C. Freshness, volume, schema, distribution monitoring. D. Pure SLA only.

Select an answer to check.

Answer: Freshness, volume, schema, distribution monitoring.

Here, Freshness, volume, schema, distribution monitoring. is the right choice. Detects issues fast. This is the most accurate statement for how is data observability best characterized. The remaining choices fail because they don’t satisfy the full definition.

Q97. Which option best describes data mesh?

A. Pure data lake only. B. Decentralized domain-owned data products. C. Pure ETL pipeline. D. Pure central warehouse.

Select an answer to check.

Answer: Decentralized domain-owned data products.

In this case, Decentralized domain-owned data products. is correct. Org/architecture pattern. This is the most accurate statement for which option best describes data mesh. The remaining choices fail because they don’t satisfy the full definition.

Q98. What is the primary purpose of data mesh?

A. Decentralized domain-owned data products. B. Pure data lake only. C. Pure central warehouse. D. Pure ETL pipeline.

Select an answer to check.

Answer: Decentralized domain-owned data products.

The best option here is Decentralized domain-owned data products.. Org/architecture pattern. This is the most accurate statement for what is the primary purpose of data mesh. The remaining choices fail because they don’t satisfy the full definition.

Q99. Which statement about data mesh is most accurate?

A. Pure data lake only. B. Pure central warehouse. C. Pure ETL pipeline. D. Decentralized domain-owned data products.

Select an answer to check.

Answer: Decentralized domain-owned data products.

For this question, Decentralized domain-owned data products. is correct. Org/architecture pattern. This is the most accurate statement for which statement about data mesh is most accurate. The remaining choices fail because they don’t satisfy the full definition.

Q100. How is data mesh best characterized?

A. Decentralized domain-owned data products. B. Pure central warehouse. C. Pure ETL pipeline. D. Pure data lake only.

Select an answer to check.

Answer: Decentralized domain-owned data products.

Decentralized domain-owned data products. is the correct answer here. Org/architecture pattern. This is the most accurate statement for how is data mesh best characterized. The remaining choices fail because they don’t satisfy the full definition.