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Data Dare data transformation L3 sticker: the findi360 mascot analysing Complex Joins, Exceptions and Transformation Logic.

DD-TRF-003

Complex Joins, Exceptions and Transformation Logic

Decide which customer tier a sale belonged to on the day it happened, which rows break the exception rules, and what survives duplicate resolution.

  • Data Transformation
  • L3 · PARQUET
  • ~514,953 rows
  • 12 tables
  • 50 questions
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v1.0 · 6 files

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  • Question Book PDF DD-TRF-003_Question_Book.pdf 1.2 MB · v1.0
  • Dataset Documentation / Data Dictionary XLSX DD-TRF-003_Data_Dictionary.xlsx 12.7 KB · v1.0
  • Business Introduction PDF DD-TRF-003_Business_Introduction.pdf 614.4 KB · v1.0
  • Relationship Diagram PDF DD-TRF-003_Relationship_Model.pdf 615.5 KB · v1.0
  • Raw fact data DD-TRF-003_FactTransformationEvents.parquet 12.6 MB · v1.0
  • Dimension / supporting data DD-TRF-003_Dimensions.zip 1.1 MB · v1.0

Questions

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  1. Q001 Easy Rows in the export file
  2. Q002 Easy Exact duplicate rows
  3. Q003 Easy Conflicting duplicate IDs
  4. Q004 Easy Blank customer codes
  5. Q005 Easy Amounts stored as text
  6. Q006 Easy Dates not in ISO format
  7. Q007 Easy Codes with stray case or spaces
  8. Q008 Easy Unknown product codes
  9. Q009 Easy Return lines
  10. Q010 Easy Valid rows after cleaning
  11. Q011 Easy Reconciled total amount
  12. Q012 Easy Distinct customers after standardising codes
  13. Q013 Medium Clean amount by month
  14. Q014 Medium Valid rows by month
  15. Q015 Medium Distinct customers by month
  16. Q016 Medium Exact duplicates by month
  17. Q017 Medium Conflicting duplicates by month
  18. Q018 Medium Blank customer codes by month
  19. Q019 Medium Text amounts by month
  20. Q020 Medium Non-ISO dates by month
  21. Q021 Medium Stray-case codes by month
  22. Q022 Medium Unknown products by month
  23. Q023 Medium Return lines by month
  24. Q024 Medium Value of returns by month
  25. Q025 Medium Year-on-year change in clean amount
  26. Q026 Medium Clean amount by category
  27. Q027 Medium Clean amount by region
  28. Q028 Medium Rows per batch file
  29. Q029 Medium Drifted columns per batch file
  30. Q030 Medium Batch rows absent from the export
  31. Q031 Hard Regions driving the year-on-year change
  32. Q032 Hard Category standardisation bridge
  33. Q033 Hard Reconcile batch Batch_2025_07 to the export
  34. Q034 Hard Reconcile batch Batch_2025_08 to the export
  35. Q035 Hard Reconcile batch Batch_2025_09 to the export
  36. Q036 Hard Reconcile batch Batch_2025_10 to the export
  37. Q037 Hard Reconcile batch Batch_2025_11 to the export
  38. Q038 Hard Reconcile batch Batch_2025_12 to the export
  39. Q039 Hard Sales by customer tier as at transaction date
  40. Q040 Hard Rows breaking the exception rules
  41. Q041 Hard Monthly rates against a flat rate
  42. Q042 Hard Top ten products before and after cleaning
  43. Q043 Very Hard Checksum of the final table
  44. Q044 Very Hard Conflicting duplicates: amount at stake
  45. Q045 Very Hard Survivorship by latest load
  46. Q046 Very Hard Customers collapsed by alias mapping
  47. Q047 Very Hard Sales re-tiered by the SCD change
  48. Q048 Very Hard Schema drift in batch Batch_2025_09
  49. Q049 Very Hard Schema drift in batch Batch_2025_12
  50. Q050 Very Hard Incremental load across all batches

General discussion

Anything about this dataset that is not one question — loading the files, which tool, how you set it up.

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