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CapGemini Spain for ENEL

Started ‎03-23-2021 by
Modified ‎10-20-2022 by
Views 1,425
Team Name CapGemini Spain for ENEL
Track Energy
Use Case Develop predictives models based on industrial KPI and historical economical results.

Data cleaning

Anomaly Detection

Machine Learning
Region EMEA
Team lead Paula
Team members Adrian, Paula, Joan, Alejandro, José Ignacio, Wilder, Gonzalo




Predict the results for Enel group based on industrial KPI and historical economical results. Cleaning the data is the first step for the team (SAS Data Studio). Through data cleaning techniques we’ll tidy our dataset so that the team can work with them. Next step is looking for errors and anomalies in the dataset to increase the accuracy of the models (SAS Analytics). Once the data is in a good state, the team will start working with different predictive algorithms and comparing its accuracy in the hope of finding a predictive model good enough (SAS Model Studio).



Great demo, congrats!

Take a look @NathalieQ

wow. and like whoa!, both, go big or ... keep tryin'/never give up! good luck, great project.

Version history
Last update:
‎10-20-2022 12:22 PM
Updated by:

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