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Pensando como um data scientist

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Pensando como um data scientist

  1. 1. pensandocomoum @andrefaria DataScientist
  2. 2. Monica Rogati,umadatascientistdoLinkedIn apresentou10errosqueempreendedoresdevemevitarao analisarosdadosdesuasstartups. vamosverquaissãoeles…
  3. 3. assumirqueosdadosestão limpos
  4. 4. NÃONORMALIZAROSDADOS
  5. 5. excluiroutliers Essas  21  pessoas  usando  seu  produto  1000x  por  dia   são  g4andes  fãs  ou  bots?  Independente  de  quem   sejam  não  os  ig<ore.  
  6. 6. incluiroutliers Cuidado  com  esses  mesmos  21  usuários  quando  estiver  fazendo   deterCinadas  análises  
  7. 7. ignorarseasonality Dia,  Mês,  Estação,  etc.  
  8. 8. ignorarotamanhoaoreportar crescimentoÉ  fácil  dobrar  de  2  para  4  usuários…  
  9. 9. Datavomit Pra  que  serNe  um  dashboard    se  não  sabe  para  onde  olhar?  
  10. 10. métricaspró-ativasdemais Você  quer  ser  responsivo  mas  cuidado  para  usar   tantos  alarCes  que  você  comece  a  ig<orá-­‐los
  11. 11. asíndromedo“nãocoletadoaqui” MistRrar  seus  dados  com  dados  exSer<os  podem   levar  a  bons  insights
  12. 12. focarnoruído Cuidado  para  não  ver  padrões  onde  não  há.  
  13. 13. aprendamais

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