Hello fellow Data Scientists,
I'm gonna ask broad questions to try to gather as much feedback as I can and then decide what to do. Everything is a possibility at this stage, there are no right or wrong. I have some data background but it's not relevant and that's why I'm a bit stuck with my thoughts.
Objective: Create kind of an Hackaton/program with a company where at the end of the day Data is transformed into relevant business insights. Those insights will be capitalized to generate possible new business models.
Some questions about:
– Should we have several teams working with data? how many people per team, 1 or more? how can they work together – can we assign several roles like: 1 to cross data, 1 to clean the data, etc (is this stupid? lol) ?
– Are these people data scientists only? Should we have 1 business guy per team to give a different perspective?
– Should we have Data Scientists in the morning and then business people during the evening?
– Should we start with raw data?
– All the teams should start with the same Data?
– Should we try to cross data from company with some public government data or other sources?
– A morning, 12h, 24h, 2 days? How much time do we need?
– Should we specify some avenues to explore or let them search for everything?
– What are the things I have to take into account?
I Know this is all too broad, vague, open and your answer will be "It all depends on what you want", but what I need here is your expertise and sensitivity. If it was you, what would you do, how and why? Do you have anything that had been done before as a good example?
Thank you so much!
submitted by /u/gonrodrigues
Source: Reddit Data Science