On the face of it, being a data professional can seem quite mechanical. It’s all SQL queries, graphs and spreadsheets right?
There’s some truth to this, but at it’s heart, great data work is about decision making. Decisions that are made by humans, in all their wonderful, enthusiastic, biased and deeply flawed goodness. This is what many analysts and data scientists who are earlier in their careers struggle with - and what catches out many fresh faces data people who find themselves suddenly as the most senior data professional in their organisation.
There are some really tough decisions right at the heart of all of this:
- Is my role to inform or to challenge?
- How much should I be a builder and how much am I an insight engine?
- What’s the right level of technical debt?
- How much should I make do with existing technology, or invest time in shifting the tooling we already have deployed?
- How do I engage the team around me in the very real prioritisation calls I’m trying to make without losing them in the technical details?
- How do I give my team confidence that their metrics are true when I know all of the caveats and fuzzy edges that were necessary to make them? How much of that should I communicate, and how much should I abstract them away from?
Some of these questions have established answers to for specific scenarios but a lot of this is judgement and perhaps even wisdom which comes from having seen similar situations play out in other organisations. Often it can also involve helping data professionals become data leaders and find their own way to that conclusions.
This is where Data Mentoring can come in. By spending time every month with data leaders in your organisation we can explore these topics in a safe space with someone who’s trodden that path in front of them. If that’s interesting - reach out, especially if you’re in the London area as we can also offer in-person mentoring sessions.
