Data ETL Quality & Validation MCQ Questions with Answers (Latest 2026)

Q1. Which option best describes data quality?

A. Pure index speed. B. Fitness of data for intended use. C. Pure schema size. D. Pure storage size.

Select an answer to check.

Answer: Fitness of data for intended use.

Here, Fitness of data for intended use. is the right choice. Multiple dimensions: accuracy, completeness, consistency. It aligns directly with what the question asks about which option best describes data quality. A quick elimination of partially true options helps confirm it.

Q2. What is the primary purpose of data quality?

A. Pure schema size. B. Pure storage size. C. Fitness of data for intended use. D. Pure index speed.

Select an answer to check.

Answer: Fitness of data for intended use.

In this case, Fitness of data for intended use. is correct. Multiple dimensions: accuracy, completeness, consistency. It aligns directly with what the question asks about what is the primary purpose of data quality. A quick elimination of partially true options helps confirm it.

Q3. Which statement about data quality is most accurate?

A. Pure storage size. B. Pure index speed. C. Pure schema size. D. Fitness of data for intended use.

Select an answer to check.

Answer: Fitness of data for intended use.

The best option here is Fitness of data for intended use.. Multiple dimensions: accuracy, completeness, consistency. It aligns directly with what the question asks about which statement about data quality is most accurate. A quick elimination of partially true options helps confirm it.

Q4. How is data quality best characterized?

A. Pure index speed. B. Pure schema size. C. Fitness of data for intended use. D. Pure storage size.

Select an answer to check.

Answer: Fitness of data for intended use.

For this question, Fitness of data for intended use. is correct. Multiple dimensions: accuracy, completeness, consistency. It aligns directly with what the question asks about how is data quality best characterized. A quick elimination of partially true options helps confirm it.

Q5. Which option best describes completeness?

A. Pure validity. B. Required fields are non-null and present. C. Pure timeliness. D. Pure uniqueness.

Select an answer to check.

Answer: Required fields are non-null and present.

Required fields are non-null and present. is the correct answer here. Tracked per column. It aligns directly with what the question asks about which option best describes completeness. A quick elimination of partially true options helps confirm it.

Q6. What is the primary purpose of completeness?

A. Pure validity. B. Required fields are non-null and present. C. Pure timeliness. D. Pure uniqueness.

Select an answer to check.

Answer: Required fields are non-null and present.

Here, Required fields are non-null and present. is the right choice. Tracked per column. This matches the core idea being tested around what is the primary purpose of completeness. A quick elimination of partially true options helps confirm it.

Q7. Which statement about completeness is most accurate?

A. Pure uniqueness. B. Pure timeliness. C. Required fields are non-null and present. D. Pure validity.

Select an answer to check.

Answer: Required fields are non-null and present.

In this case, Required fields are non-null and present. is correct. Tracked per column. This matches the core idea being tested around which statement about completeness is most accurate. A quick elimination of partially true options helps confirm it.

Q8. How is completeness best characterized?

A. Pure timeliness. B. Pure uniqueness. C. Required fields are non-null and present. D. Pure validity.

Select an answer to check.

Answer: Required fields are non-null and present.

The best option here is Required fields are non-null and present.. Tracked per column. This matches the core idea being tested around how is completeness best characterized. A quick elimination of partially true options helps confirm it.

Q9. Which option best describes uniqueness?

A. Pure validity. B. Pure consistency. C. Pure completeness. D. Keys/IDs are unique where required.

Select an answer to check.

Answer: Keys/IDs are unique where required.

For this question, Keys/IDs are unique where required. is correct. Detect via row counts vs distinct. This matches the core idea being tested around which option best describes uniqueness. A quick elimination of partially true options helps confirm it.

Q10. What is the primary purpose of uniqueness?

A. Pure completeness. B. Keys/IDs are unique where required. C. Pure consistency. D. Pure validity.

Select an answer to check.

Answer: Keys/IDs are unique where required.

Keys/IDs are unique where required. is the correct answer here. Detect via row counts vs distinct. This matches the core idea being tested around what is the primary purpose of uniqueness. A quick elimination of partially true options helps confirm it.

Q11. Which statement about uniqueness is most accurate?

A. Pure consistency. B. Pure validity. C. Pure completeness. D. Keys/IDs are unique where required.

Select an answer to check.

Answer: Keys/IDs are unique where required.

Here, Keys/IDs are unique where required. is the right choice. Detect via row counts vs distinct. That is exactly the concept behind which statement about uniqueness is most accurate in this context. A quick elimination of partially true options helps confirm it.

Q12. How is uniqueness best characterized?

A. Pure consistency. B. Pure validity. C. Keys/IDs are unique where required. D. Pure completeness.

Select an answer to check.

Answer: Keys/IDs are unique where required.

In this case, Keys/IDs are unique where required. is correct. Detect via row counts vs distinct. That is exactly the concept behind how is uniqueness best characterized in this context. A quick elimination of partially true options helps confirm it.

Q13. Which option best describes validity?

A. Pure uniqueness. B. Pure completeness. C. Pure timeliness. D. Values match expected types/ranges/regex.

Select an answer to check.

Answer: Values match expected types/ranges/regex.

The best option here is Values match expected types/ranges/regex.. Enforced by schemas/constraints. That is exactly the concept behind which option best describes validity in this context. A quick elimination of partially true options helps confirm it.

Q14. What is the primary purpose of validity?

A. Pure timeliness. B. Values match expected types/ranges/regex. C. Pure completeness. D. Pure uniqueness.

Select an answer to check.

Answer: Values match expected types/ranges/regex.

For this question, Values match expected types/ranges/regex. is correct. Enforced by schemas/constraints. That is exactly the concept behind what is the primary purpose of validity in this context. A quick elimination of partially true options helps confirm it.

Q15. Which statement about validity is most accurate?

A. Pure timeliness. B. Values match expected types/ranges/regex. C. Pure uniqueness. D. Pure completeness.

Select an answer to check.

Answer: Values match expected types/ranges/regex.

Values match expected types/ranges/regex. is the correct answer here. Enforced by schemas/constraints. That is exactly the concept behind which statement about validity is most accurate in this context. A quick elimination of partially true options helps confirm it.

Q16. How is validity best characterized?

A. Pure uniqueness. B. Pure timeliness. C. Values match expected types/ranges/regex. D. Pure completeness.

Select an answer to check.

Answer: Values match expected types/ranges/regex.

Here, Values match expected types/ranges/regex. is the right choice. Enforced by schemas/constraints. It fits the requirement in the prompt about how is validity best characterized. A quick elimination of partially true options helps confirm it.

Q17. Which option best describes consistency?

A. Pure validity. B. Same data agrees across sources/joins. C. Pure uniqueness. D. Pure completeness.

Select an answer to check.

Answer: Same data agrees across sources/joins.

In this case, Same data agrees across sources/joins. is correct. Cross-table checks. It fits the requirement in the prompt about which option best describes consistency. A quick elimination of partially true options helps confirm it.

Q18. What is the primary purpose of consistency?

A. Same data agrees across sources/joins. B. Pure validity. C. Pure completeness. D. Pure uniqueness.

Select an answer to check.

Answer: Same data agrees across sources/joins.

The best option here is Same data agrees across sources/joins.. Cross-table checks. It fits the requirement in the prompt about what is the primary purpose of consistency. A quick elimination of partially true options helps confirm it.

Q19. Which statement about consistency is most accurate?

A. Same data agrees across sources/joins. B. Pure validity. C. Pure uniqueness. D. Pure completeness.

Select an answer to check.

Answer: Same data agrees across sources/joins.

For this question, Same data agrees across sources/joins. is correct. Cross-table checks. It fits the requirement in the prompt about which statement about consistency is most accurate. A quick elimination of partially true options helps confirm it.

Q20. How is consistency best characterized?

A. Pure uniqueness. B. Pure validity. C. Same data agrees across sources/joins. D. Pure completeness.

Select an answer to check.

Answer: Same data agrees across sources/joins.

Same data agrees across sources/joins. is the correct answer here. Cross-table checks. It fits the requirement in the prompt about how is consistency best characterized. A quick elimination of partially true options helps confirm it.

Q21. Which option best describes timeliness?

A. Data is fresh enough for its use. B. Pure index speed. C. Pure schema age. D. Pure size.

Select an answer to check.

Answer: Data is fresh enough for its use.

Here, Data is fresh enough for its use. is the right choice. Often time-since-load metric. This is the most accurate statement for which option best describes timeliness. A quick elimination of partially true options helps confirm it.

Q22. What is the primary purpose of timeliness?

A. Pure schema age. B. Pure index speed. C. Pure size. D. Data is fresh enough for its use.

Select an answer to check.

Answer: Data is fresh enough for its use.

In this case, Data is fresh enough for its use. is correct. Often time-since-load metric. This is the most accurate statement for what is the primary purpose of timeliness. A quick elimination of partially true options helps confirm it.

Q23. Which statement about timeliness is most accurate?

A. Pure size. B. Pure schema age. C. Data is fresh enough for its use. D. Pure index speed.

Select an answer to check.

Answer: Data is fresh enough for its use.

The best option here is Data is fresh enough for its use.. Often time-since-load metric. This is the most accurate statement for which statement about timeliness is most accurate. A quick elimination of partially true options helps confirm it.

Q24. How is timeliness best characterized?

A. Data is fresh enough for its use. B. Pure schema age. C. Pure size. D. Pure index speed.

Select an answer to check.

Answer: Data is fresh enough for its use.

For this question, Data is fresh enough for its use. is correct. Often time-since-load metric. This is the most accurate statement for how is timeliness best characterized. A quick elimination of partially true options helps confirm it.

Q25. Which option best describes accuracy?

A. Pure timeliness. B. Pure consistency. C. Pure validity. D. Data correctly reflects reality.

Select an answer to check.

Answer: Data correctly reflects reality.

Data correctly reflects reality. is the correct answer here. Hardest to measure directly. This is the most accurate statement for which option best describes accuracy. A quick elimination of partially true options helps confirm it.

Q26. What is the primary purpose of accuracy?

A. Pure timeliness. B. Data correctly reflects reality. C. Pure validity. D. Pure consistency.

Select an answer to check.

Answer: Data correctly reflects reality.

Here, Data correctly reflects reality. is the right choice. Hardest to measure directly. It aligns directly with what the question asks about what is the primary purpose of accuracy. The other options are either incomplete or contextually incorrect.

Q27. Which statement about accuracy is most accurate?

A. Pure consistency. B. Data correctly reflects reality. C. Pure validity. D. Pure timeliness.

Select an answer to check.

Answer: Data correctly reflects reality.

In this case, Data correctly reflects reality. is correct. Hardest to measure directly. It aligns directly with what the question asks about which statement about accuracy is most accurate. The other options are either incomplete or contextually incorrect.

Q28. How is accuracy best characterized?

A. Pure timeliness. B. Data correctly reflects reality. C. Pure validity. D. Pure consistency.

Select an answer to check.

Answer: Data correctly reflects reality.

The best option here is Data correctly reflects reality.. Hardest to measure directly. It aligns directly with what the question asks about how is accuracy best characterized. The other options are either incomplete or contextually incorrect.

Q29. Which option best describes schema validation?

A. Pure value range only. B. Verify columns/types match expected schema. C. Pure uniqueness only. D. Pure null-only checks.

Select an answer to check.

Answer: Verify columns/types match expected schema.

For this question, Verify columns/types match expected schema. is correct. Catch breaking changes. It aligns directly with what the question asks about which option best describes schema validation. The other options are either incomplete or contextually incorrect.

Q30. What is the primary purpose of schema validation?

A. Pure value range only. B. Pure uniqueness only. C. Pure null-only checks. D. Verify columns/types match expected schema.

Select an answer to check.

Answer: Verify columns/types match expected schema.

Verify columns/types match expected schema. is the correct answer here. Catch breaking changes. It aligns directly with what the question asks about what is the primary purpose of schema validation. The other options are either incomplete or contextually incorrect.

Q31. Which statement about schema validation is most accurate?

A. Verify columns/types match expected schema. B. Pure null-only checks. C. Pure value range only. D. Pure uniqueness only.

Select an answer to check.

Answer: Verify columns/types match expected schema.

Here, Verify columns/types match expected schema. is the right choice. Catch breaking changes. This matches the core idea being tested around which statement about schema validation is most accurate. The other options are either incomplete or contextually incorrect.

Q32. How is schema validation best characterized?

A. Verify columns/types match expected schema. B. Pure null-only checks. C. Pure uniqueness only. D. Pure value range only.

Select an answer to check.

Answer: Verify columns/types match expected schema.

In this case, Verify columns/types match expected schema. is correct. Catch breaking changes. This matches the core idea being tested around how is schema validation best characterized. The other options are either incomplete or contextually incorrect.

Q33. Which option best describes Great Expectations?

A. A vector DB. B. A logger. C. Open-source data validation framework. D. A web framework.

Select an answer to check.

Answer: Open-source data validation framework.

The best option here is Open-source data validation framework.. Expectation suites. This matches the core idea being tested around which option best describes great expectations. The other options are either incomplete or contextually incorrect.

Q34. What is the primary purpose of Great Expectations?

A. A web framework. B. A vector DB. C. A logger. D. Open-source data validation framework.

Select an answer to check.

Answer: Open-source data validation framework.

For this question, Open-source data validation framework. is correct. Expectation suites. This matches the core idea being tested around what is the primary purpose of great expectations. The other options are either incomplete or contextually incorrect.

Q35. Which statement about Great Expectations is most accurate?

A. A vector DB. B. A logger. C. A web framework. D. Open-source data validation framework.

Select an answer to check.

Answer: Open-source data validation framework.

Open-source data validation framework. is the correct answer here. Expectation suites. This matches the core idea being tested around which statement about great expectations is most accurate. The other options are either incomplete or contextually incorrect.

Q36. How is Great Expectations best characterized?

A. Open-source data validation framework. B. A vector DB. C. A web framework. D. A logger.

Select an answer to check.

Answer: Open-source data validation framework.

Here, Open-source data validation framework. is the right choice. Expectation suites. That is exactly the concept behind how is great expectations best characterized in this context. The other options are either incomplete or contextually incorrect.

Q37. Which option best describes dbt tests?

A. A pure web framework. B. Unit-test-style SQL data tests. C. A pure logger. D. A pure profiler.

Select an answer to check.

Answer: Unit-test-style SQL data tests.

In this case, Unit-test-style SQL data tests. is correct. Generic and singular tests. That is exactly the concept behind which option best describes dbt tests in this context. The other options are either incomplete or contextually incorrect.

Q38. What is the primary purpose of dbt tests?

A. A pure logger. B. Unit-test-style SQL data tests. C. A pure profiler. D. A pure web framework.

Select an answer to check.

Answer: Unit-test-style SQL data tests.

The best option here is Unit-test-style SQL data tests.. Generic and singular tests. That is exactly the concept behind what is the primary purpose of dbt tests in this context. The other options are either incomplete or contextually incorrect.

Q39. Which statement about dbt tests is most accurate?

A. Unit-test-style SQL data tests. B. A pure web framework. C. A pure profiler. D. A pure logger.

Select an answer to check.

Answer: Unit-test-style SQL data tests.

For this question, Unit-test-style SQL data tests. is correct. Generic and singular tests. That is exactly the concept behind which statement about dbt tests is most accurate in this context. The other options are either incomplete or contextually incorrect.

Q40. How is dbt tests best characterized?

A. A pure web framework. B. A pure logger. C. A pure profiler. D. Unit-test-style SQL data tests.

Select an answer to check.

Answer: Unit-test-style SQL data tests.

Unit-test-style SQL data tests. is the correct answer here. Generic and singular tests. That is exactly the concept behind how is dbt tests best characterized in this context. The other options are either incomplete or contextually incorrect.

Q41. Which option best describes anomaly detection in data?

A. Pure null checks. B. Flag unusual distribution shifts. C. Pure schema checks only. D. Pure uniqueness.

Select an answer to check.

Answer: Flag unusual distribution shifts.

Here, Flag unusual distribution shifts. is the right choice. Distinct from per-row checks. It fits the requirement in the prompt about which option best describes anomaly detection in data. The other options are either incomplete or contextually incorrect.

Q42. What is the primary purpose of anomaly detection in data?

A. Pure null checks. B. Pure schema checks only. C. Pure uniqueness. D. Flag unusual distribution shifts.

Select an answer to check.

Answer: Flag unusual distribution shifts.

In this case, Flag unusual distribution shifts. is correct. Distinct from per-row checks. It fits the requirement in the prompt about what is the primary purpose of anomaly detection. The other options are either incomplete or contextually incorrect.

Q43. Which statement about anomaly detection in data is most accurate?

A. Pure uniqueness. B. Flag unusual distribution shifts. C. Pure schema checks only. D. Pure null checks.

Select an answer to check.

Answer: Flag unusual distribution shifts.

The best option here is Flag unusual distribution shifts.. Distinct from per-row checks. It fits the requirement in the prompt about which statement about anomaly detection in data is. The other options are either incomplete or contextually incorrect.

Q44. How is anomaly detection in data best characterized?

A. Pure schema checks only. B. Flag unusual distribution shifts. C. Pure uniqueness. D. Pure null checks.

Select an answer to check.

Answer: Flag unusual distribution shifts.

For this question, Flag unusual distribution shifts. is correct. Distinct from per-row checks. It fits the requirement in the prompt about how is anomaly detection in data best characterized. The other options are either incomplete or contextually incorrect.

Q45. Which option best describes freshness SLAs?

A. Pure error rate. B. Pure latency only. C. Pure throughput only. D. Time since last successful load.

Select an answer to check.

Answer: Time since last successful load.

Time since last successful load. is the correct answer here. Customer-facing metric. It fits the requirement in the prompt about which option best describes freshness slas. The other options are either incomplete or contextually incorrect.

Q46. What is the primary purpose of freshness SLAs?

A. Pure error rate. B. Pure throughput only. C. Time since last successful load. D. Pure latency only.

Select an answer to check.

Answer: Time since last successful load.

Here, Time since last successful load. is the right choice. Customer-facing metric. This is the most accurate statement for what is the primary purpose of freshness slas. The other options are either incomplete or contextually incorrect.

Q47. Which statement about freshness SLAs is most accurate?

A. Pure latency only. B. Pure throughput only. C. Pure error rate. D. Time since last successful load.

Select an answer to check.

Answer: Time since last successful load.

In this case, Time since last successful load. is correct. Customer-facing metric. This is the most accurate statement for which statement about freshness slas is most accurate. The other options are either incomplete or contextually incorrect.

Q48. How is freshness SLAs best characterized?

A. Pure error rate. B. Pure latency only. C. Pure throughput only. D. Time since last successful load.

Select an answer to check.

Answer: Time since last successful load.

The best option here is Time since last successful load.. Customer-facing metric. This is the most accurate statement for how is freshness slas best characterized. The other options are either incomplete or contextually incorrect.

Q49. Which option best describes row count delta?

A. Pure null fraction only. B. Pure unique count only. C. Change in row count vs previous run. D. Pure schema size.

Select an answer to check.

Answer: Change in row count vs previous run.

For this question, Change in row count vs previous run. is correct. Catches major regressions. This is the most accurate statement for which option best describes row count delta. The other options are either incomplete or contextually incorrect.

Q50. What is the primary purpose of row count delta?

A. Pure unique count only. B. Pure null fraction only. C. Pure schema size. D. Change in row count vs previous run.

Select an answer to check.

Answer: Change in row count vs previous run.

Change in row count vs previous run. is the correct answer here. Catches major regressions. This is the most accurate statement for what is the primary purpose of row count. The other options are either incomplete or contextually incorrect.