In the world of finance, every bank strives to retain its customers, ensuring the sustainability of their business. This was especially true for an anonymous multinational bank, which understood that acquiring new clients was far more costly than retaining existing ones. The bank knew that understanding why clients decided to leave was crucial for developing effective loyalty programs and retention campaigns.

Tom, a dedicated data engineer at the bank, was tasked with a critical project. He needed to create a test file to validate the data pipeline he had built for the bank’s data warehouse. This data warehouse was a powerful tool that allowed the business to analyze patterns and reasons behind client churn, providing valuable insights to prevent it.

To accomplish this, Tom turned to ParroFile, a free online data generation tool capable of generating test files in the PARQUET format. The business analyst had specified the requirements, and ParroFile was known for its accuracy, ensuring that Tom could test every piece of logic in the data pipeline thoroughly.

After setting up the parameters, Tom ran ParroFile and watched as it generated the test file. He then integrated this file into the data pipeline, running various tests to ensure everything functioned perfectly. The data flowed seamlessly, and the logic checks passed with flying colors.

  • RowNumber The record (row) number and has no effect on the output.
  • CustomerId Contains random values and has no effect on customer leaving the bank.
  • Surname The surname of a customer has no impact on their decision to leave the bank
  • CreditScore Can have an effect on customer churn, since a customer with a higher credit score is less likely to leave the bank.
  • Geography Customer’s location can affect their decision to leave the bank.
  • Gender It’s interesting to explore whether gender plays a role in a customer leaving the bank.
  • Age This is certainly relevant, since older customers are less likely to leave their bank than younger ones.
  • Tenure Refers to the number of years that the customer has been a client of the bank. Normally, older clients are more loyal and less likely to leave a bank.
  • Balance Also a very good indicator of customer churn, as people with a higher balance in their accounts are less likely to leave the bank compared to those with lower balances.
  • NumOfProducts Refers to the number of products that a customer has purchased through the bank.
  • HasCrCard Denotes whether or not a customer has a credit card. This column is also relevant, since people with a credit card are less likely to leave the bank.
  • IsActiveMember Active customers are less likely to leave the bank.
  • EstimatedSalary As with balance, people with lower salaries are more likely to leave the bank compared to those with higher salaries.
  • Exited Whether or not the customer left the bank.
  • Complain Customer has complaint or not.
  • SatisfactionScore Score provided by the customer for their complaint resolution.
  • CardType Type of card hold by the customer.
  • PointsEarned The points earned by the customer for using credit card.
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With his task successfully completed, Tom leaned back in his chair, a sense of accomplishment washing over him. He reached for his favorite mug and poured himself a nice cup of tea. As he sipped the warm beverage, he felt a deep satisfaction, knowing that his work would help the bank retain its valued customers and thrive in the competitive financial landscape.