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Bank-campaign-dataset-insights

This task was given to me as part of a datascience boot camp.

The brief

This dataset corresponds to a bank's marketing campaign based on phone calls. There are 41188 instances and 21 attributes in this dataset. You are given multiple files corresponding to the clients.

Analyse the data. The ultimate goal of the campaign was to get customers to sign up to a product. Look at the data and try to make sense of it.

  • what are the most interesting features and why?
  • does the data need to be transformed or adjusted? why and how?
  • from exploring the data, can you build a few key insights that could be shared with a data-curious executive who has not looked at the data?
  • once you have pre-processed the data (aim of the exercise) what are your suggestions for the next steps (note: you do not need to do these next steps but rather imagine what could be done with the data now that you have explored it and make suggestions)

So this is a data exploration exercise, not a modeling one. I have performed all analysis in the insights notebook.

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