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How to address the blind spots of data scientists

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Contenido proporcionado por Data Transformers Podcast. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Data Transformers Podcast o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
A good data scientist is not only good at coding, tweaking models but is also good at assessing the outputs of the models in the context of business decisions. As data scientists spend upto 80% of their time data munging, they will be better off spending some quality upfront time with the business leaders asking questions about the customer journey and how the data is collected along the way. Even though the data scientists are not expected to be business domain experts, they should think of their output in the context of business outcomes and communicate their results in business terms. The episode also emphasizes the need for all types and sizes of companies to get acquainted with analytics or fall behind.
  continue reading

50 episodios

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Manage episode 305902503 series 2927369
Contenido proporcionado por Data Transformers Podcast. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Data Transformers Podcast o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
A good data scientist is not only good at coding, tweaking models but is also good at assessing the outputs of the models in the context of business decisions. As data scientists spend upto 80% of their time data munging, they will be better off spending some quality upfront time with the business leaders asking questions about the customer journey and how the data is collected along the way. Even though the data scientists are not expected to be business domain experts, they should think of their output in the context of business outcomes and communicate their results in business terms. The episode also emphasizes the need for all types and sizes of companies to get acquainted with analytics or fall behind.
  continue reading

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