Create a series of questions related to the analysis goals you would like to answer, and note the dimensions you’re interested in exploring within, i.e., specific time periods, new users, users in a certain age bracket or geographical area, etc.Example: for an analysis on user engagement, a product manager may want to know how many times new users typically visit your website in their first versus second month.Collect any previous research, organizational lore, and widely accepted assumptions related to the analysis topic. Review what’s been previously researched or analyzed to understand what is already known in this arena.Make note of whether there are historical answers to any of your analysis questions. Note: when you’re determining how relevant those answers are, consider the amount of time since any previous analysis, and whether there have been significant changes in the analysis population or product/ service since then.Example: Keeping to the new user activity idea, maybe someone did an analysis two years ago that identified that users’ activity tapered off and plateaued 5 weeks after account creation. If the company introduced a new 6-week drip campaign for new users a year ago, this insight may not be relevant any longer.Once you’ve synthesized your goals and key questions, you can identify what relevant data is easily available, and what supplemental data is potentially accessible. Verify your permissions to each data source, and request access from data/ process owners for any supplemental datasets. Spend some time familiarizing yourself with the datasets, and rule out any questions on your list it’s not possible to answer with the data you have.Do a prioritization exercise with the key stakeholder(s), for example, a product manager, to understand which questions they believe are most important. It’s a good idea to T-shirt size (S, M, L) the complexity of the questions on your list before this conversation to illustrate the level of effort to answer them. If the questions on your list are more work than is feasible in a single analysis, use those prioritizations to determine how to stagger them into multiple analyses.