CapGemini Spain for ENEL

[#1]

Team Name	CapGemini Spain for ENEL
Track	Energy
Use Case	Develop predictives models based on industrial KPI and historical economical results.
Technology	Data cleaning Anomaly Detection Machine Learning
Region	EMEA
Team lead	Paula
Team members	Adrian, Paula, Joan, Alejandro, José Ignacio, Wilder, Gonzalo

Description

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).

[EduvigisOrtiz]

Great demo, congrats!

[EduvigisOrtiz]

Take a look @NathalieQ

[fikramulla2]

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