If you go to your stored links on your browser right now, I’d bet that you have at least 5-10 links that go to dashboards, data tables, reports, experiment readouts or ML model summaries. We have no lack of data assets. Those assets at different points in time helped us make a decision, provide a recommendation, create an insight or bail on a project altogether. Those data assets existed at a particular moment in time to do a particular task. Then they make a one way trip to the “graveyard dashboard” or “land of forgotten experiments”.
As you mentioned in number 5, choosing to stop maintaining a data product that is dear to our heart is very painful. And I think many organizations and of course people within them have a hard time doing it. How can someone lower in the business hierarchy (ie. Data Scientist) convince management that it's time to let go of the data product we made during the previous years?
Thank you Eric for sharing your thoughts.
As you mentioned in number 5, choosing to stop maintaining a data product that is dear to our heart is very painful. And I think many organizations and of course people within them have a hard time doing it. How can someone lower in the business hierarchy (ie. Data Scientist) convince management that it's time to let go of the data product we made during the previous years?
Thank you for Sharing Eric.