Do you agree with, I can definitely envision scenarios where a data analyst would like to just take the results, visualize them, give them to management or the stakeholders and move on. Certainly sometimes this can be the case, but many times you need to go back and reevaluate the data that was used and make sure the testing was thorough enough. One hypothetical situation here would be if your task was to analyze how effective a new remote working policy is on employee productivity. Your hypotheses here is that remote work has significantly decreased employee productivity. A couple of factors that could affect the data used in testing are: 1. What kind of tools/resources do the employees have at home versus in the office and how does this affect productivity? 2. What is the effect of work-life balance and how does this affect productivity? If we found out that the data we had was inadequate we could reach out to employees and get feedback on their remote working experience, how productive they feel, and if they have any blockers. Another option would simply be to extend the data collection window, allow for more time so we can collect more