The Mentoring Experiment
As I have progressed through my career, I’ve worked hard, read and studied constantly, and asked lots of questions of others. All that has helped me to improve my skills and better understand my craft. However there is more to growing a data professional career than just learning to better work with the technology.
One thing that helped me a few times was the ability to talk to other people in my companies that were more experienced in life and business. These were people that I reported to, directly or indirectly, who were willing to listen and offer me some insight and advice on my career. They were mentors, but unfortunately they were few and far between in my career.
It made me wonder if I might have made some better decisions, or made different decisions earlier in my career if I had been able to call on a mentor more regularly. Andy Warren (LinkedIn | Blog | @sqlandy) and I talked about this being a problem that we both shared in our careers, and one that we see many people struggling with today. Our discussions led us to wonder if there might be a way to develop a mentoring framework that would help people grow their careers in a way that is better suited to each individual.
The Mentoring Experiment is our initial attempt to build such a framework. It’s a short cycle, with the idea that we are seeking to learn some lessons about mentoring while helping people with advice and insight from mentors that we respect. We hope that we can find some patterns that allow us to facilitate the bonding of mentors with mentees.
We are taking applications until Apr 30, and while Andy and I will be mentoring people, we have a list of mentors from the SQL Server community that we respect and think will be good mentors for data professionals looking for help in better understanding their careers and where they want to go in the future.
We’ll be blogging about the process, respecting everyone’s privacy along the way, and we hope to expand and grow this experiment over the next few years into something that gives back to the community, and hopefully helps many data professionals grow careers that they benefit from and greatly enjoy.