Data science, data engineering, analytics, etc. aren’t very diverse. If your organization is committed to diversity and inclusion, how do you ensure you don’t replicate this problem?
The key: don’t make diversity an afterthought. As you are trying to grow an ecosystem of power users, design in diversity from the ground up.
Sometimes even simple steps can make a big difference. For example, in most organizations the administrative staff are more diverse than the IT department, business analysts, etc., and plenty of administrative staff already work with data and would like to do a lot more with it. So as you are training & mentoring power users, focus some of your efforts on recruiting a diverse group of candidates from your administrative staff. Not only will you end up with a more diverse group of power users, but you now have a pool of diverse recruits from which you can identiy and train people to eventually become data scientists and engineers.