Easy Data Engineer questions

34 questions · 5 points each for a correct first answer.

1. 1.ETL vs ELTetl, data-pipelineseasy
2. 2.Why Parquet for analyticsfile-formatseasy
3. 3.Fact and dimension tablesdata-modelingeasy
4. 4.Idempotent pipelinesdata-pipelines, reliabilityeasy
5. 5.What is a DAGorchestrationeasy
6. 6.Purpose of a primary keydata-modeling, sqleasy
7. 7.When streaming is neededstreamingeasy
8. 8.Partitioning a big tableperformance, data-modelingeasy
9. 9.Row count of a LEFT JOINsql, joinseasy
10. 10.Filtering with = NULLsql, null-handlingeasy
11. 11.COUNT(*) vs COUNT(column)sql, aggregationeasy
12. 12.Filtering groups with HAVINGsql, aggregationeasy
13. 13.Adding a number to NULLsql, null-handlingeasy
14. 14.Star vs snowflake schemadata-modelingeasy
15. 15.Grain of a fact tabledata-modelingeasy
16. 16.Why use surrogate keysdata-modeling, surrogate-keyseasy
17. 17.SCD type that overwritesscd, data-modelingeasy
18. 18.Goal of normalisationdata-modeling, normalisationeasy
19. 19.Row store or column storefile-formats, databaseseasy
20. 20.Weaknesses of CSVfile-formatseasy
21. 21.Where Avro fitsfile-formats, kafkaeasy
22. 22.Kafka consumer groupskafka, streamingeasy
23. 23.What a Kafka offset iskafkaeasy
24. 24.Retrying flaky Airflow tasksairflow, orchestrationeasy
25. 25.What an Airflow sensor doesairflow, orchestrationeasy
26. 26.Reading a cron scheduleairflow, schedulingeasy
27. 27.When Spark actually runssparkeasy
28. 28.What a Spark partition issparkeasy
29. 29.What a dbt model isdbteasy
30. 30.Built-in dbt testsdbt, data-qualityeasy
31. 31.Data lake vs warehousedata-lake, warehousingeasy
32. 32.How object storage workscloud-storageeasy
33. 33.Protecting PII in analyticsgovernance, piieasy
34. 34.A CSV bigger than memorypython, pandaseasy