Create Bank DB denormalized for ML task
The aim of this project is the creation of a denormalized table for the customer behavior analysis of a bank, starting from the database contained in the file db_bancario.sql
, which provides information on the accounts and the transactions of the customers of a bank. The resulting table contains the features for a potential supervised learning model.
The database is made up of 5 tables:
-
cliente
: -
conto
: -
tipo_conto
: -
transazioni
: -
tipo_transazione
:
The result of the project is a denormalized table, exported to a CSV file called denormalized_table.csv
, whose fields are:
- the customer age;
- the total number of outgoing transactions;
- the total number of incoming transactions;
- the total expenditure;
- the total income;
- the total number of accounts;
- the total number of accounts by type (one indicator per type);
- the total number of outgoing transactions by type (one indicator per type);
- the total number of incoming transactions by type (one indicator per type);
- the total expenditure by account type (one indicator per type);
- the total income by account type (one indicator per type).