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Data Dare data transformation L4 sticker: the findi360 mascot analysing Enterprise Data Transformation and Performance Lab.

DD-TRF-004

Enterprise Data Transformation and Performance Lab

Decide what each monthly partition adds that the export does not yet hold, which partitions drifted, and whether the pipeline reconciles at scale.

  • Data Transformation
  • L4 · PARQUET
  • ~6,179,937 rows
  • 18 tables
  • 60 questions
Get the data 60 questions

Get the data

v1.0 · 6 files

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  • Question Book PDF DD-TRF-004_Question_Book.pdf 1.3 MB · v1.0
  • Dataset Documentation / Data Dictionary XLSX DD-TRF-004_Data_Dictionary.xlsx 14.1 KB · v1.0
  • Business Introduction PDF DD-TRF-004_Business_Introduction.pdf 614.6 KB · v1.0
  • Relationship Diagram PDF DD-TRF-004_Relationship_Model.pdf 616.1 KB · v1.0
  • Raw fact data DD-TRF-004_FactDataPipelineEvents.parquet 139.3 MB · v1.0
  • Dimension / supporting data DD-TRF-004_Supporting_Tables.zip 16.3 MB · v1.0

Questions

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  1. Q007 Medium Clean amount by month
  2. Q008 Medium Valid rows by month
  3. Q009 Medium Distinct customers by month
  4. Q010 Medium Exact duplicates by month
  5. Q011 Medium Conflicting duplicates by month
  6. Q012 Medium Blank customer codes by month
  7. Q013 Medium Text amounts by month
  8. Q014 Medium Non-ISO dates by month
  9. Q015 Medium Stray-case codes by month
  10. Q016 Medium Unknown products by month
  11. Q017 Medium Return lines by month
  12. Q018 Medium Value of returns by month
  13. Q019 Medium Year-on-year change in clean amount
  14. Q020 Medium Clean amount by category
  15. Q021 Medium Clean amount by region

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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