To find all possible insights (minimum of 5) from two years of customer transaction details.

To evaluate the thinking capacity and analytical skills of the candidate.

The dataset is available at the following link:
Online Retail Dataset

  • Shape: (1,067,371 rows, 8 columns)
  • Columns:
    1. InvoiceNo: Unique invoice number. If it starts with 'C', it's a cancellation.
    2. StockCode: Unique product code.
    3. Description: Product name.
    4. Quantity: Number of items per transaction.
    5. InvoiceDate: Date and time of the transaction.
    6. UnitPrice: Price per unit in sterling (£).
    7. CustomerID: Unique customer identifier.
    8. Country: The customer's country of residence.
  • Visualisation to understand customer behaviour and identify key takeaways.
  • You are requested to share the `.sql`, `.py`, or `.ipynb` file to evaluate the result.
  • Share your methodology, results, and recommendations in a presentation.