• Data mining and analysis of the data of budgets, policies, and policy requests. Evolution of the portfolio and reporting.
  • Advanced analytics applying automatic learning methods to divide clients into homogeneous groups, to predict clients with risk of abandonment and for cross-selling


  • We extract data with ETL from the databases of Oracle, and from a process of daily ETL, we extract the data to load it in a Data Warehouse. We use BigQuery for this and to make inquiries to develop reports with Data Studio.
  • We use pre-established models of advanced analytics in BigQuery of regression of abandonment and cross-selling, and K-means for the segmentation of client groups.
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