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Data Dare retail L4 sticker: the findi360 mascot analysing Enterprise Retail Profitability and Inventory Optimisation.

DD-RET-004

Enterprise Retail Profitability and Inventory Optimisation

Decide where actuals miss budget and whether volume or price is to blame, which suppliers put availability at risk, and where inventory should sit.

  • Retail
  • L4 · PARQUET
  • ~6,000,000 rows
  • 18 tables
  • 60 questions

Get the data

v1.0 · 6 files

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  • Question Book PDF DD-RET-004_Question_Book.pdf 1.3 MB · v1.0
  • Dataset Documentation / Data Dictionary XLSX DD-RET-004_Data_Dictionary.xlsx 15.3 KB · v1.0
  • Business Introduction PDF DD-RET-004_Business_Introduction.pdf 614.1 KB · v1.0
  • Relationship Diagram PDF DD-RET-004_Relationship_Model.pdf 618.9 KB · v1.0
  • Raw fact data DD-RET-004_FactSalesTransactions.parquet 195.7 MB · v1.0
  • Dimension / supporting data DD-RET-004_Supporting_Tables.zip 42 MB · v1.0

Questions

Open one to discuss it
  1. Q040 Very Hard Choose a forecast method for next month
  2. Q041 Very Hard Outlier months in net sales
  3. Q042 Very Hard Executive scorecard
  4. Q043 Very Hard Acquisition cohort value
  5. Q044 Very Hard Cost to serve by payment method
  6. Q045 Very Hard Channel-category margin matrix
  7. Q046 Very Hard Return behaviour by loyalty tier
  8. Q047 Very Hard Slowest inventory turn by category
  9. Q048 Very Hard Budget variance decomposition
  10. Q049 Very Hard Worst month against budget
  11. Q050 Very Hard Critical supplier risk
  12. Q051 Very Hard Warehouse throughput versus capacity
  13. Q052 Very Hard Five-year margin CAGR by category
  14. Q053 Very Hard Most seasonal category
  15. Q054 Very Hard Department margin versus budget
  16. Q055 Very Hard Chronic stockout products
  17. Q056 Very Hard Cost centre margin league
  18. Q057 Very Hard Online return-rate trend
  19. Q058 Very Hard Promotion return on discount
  20. Q059 Very Hard Store budget attainment league
  21. Q060 Very Hard Supplier concentration risk

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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