Starting with Curiosity: The First Step — Tip #1
30 tips from Personal, Company, and Community Spheres
I’ve been a product manager learning about data since 2019, and it’s been a fun journey! 😻. In this series of posts, I want to share 30 tips that I’ve found useful from 3 perspectives,
- Personal
- Team & Company
- Community
These 3 aspects represents stages that you would encounter in your journey to becoming a data practitioner.
Let’s start with the first one.
#1 Start with curiosity 🐣
Why do you want to become a data practitioner? This is not a career choice. Any role do analysis, more or less.
What Problem Do You Want To Resolve?
Data represents fact or evidence. It’s objective and neutral. The numbers are meaningless but meaningful to the problems you want to resolve.
I monetized a product by advertising so I need to know how much the product earned from what ad networks, ad placements, ad size, etc. The only way I knew how to do this was through spreadsheets. I ended up having a spreadsheet that had >100K rows with numerous formulas, so it took forever to open. That’s how I got started.
A colleague wanted to compare the effectiveness of media buy. Another colleague aimed to reduce her time spent on doing financial report from 1 week to 0.5 day. Yes, they could ask data team for help. However, this added a layer to their mental model. When they wanted to think differently, they needed to wait for the data team to provide the data in another way.
If the problem is crucial to you and you cannot tolerance any waiting, you must resolve it yourself. At least once, then you can delegate to others. Do you have a problem that makes you curious to know where every piece of data comes from?
Don’t Accept As It Is
A colleagues spent 6 hours to clean 1 data source and she had 10 sources per month. All she asked for was a more powerful computer so she could run the cleaning faster 😦.
“If I had asked people what they wanted, they would have said faster horses.”
- famous but maybe not by Henry Ford
Understanding more about data is one solution for her. Other solutions could include hiring more data people, outsourcing the cleaning tasks, or requesting the data team to fix this issue, etc. Why did she choose or not choose figuring out data cleaning?
Curiosity Extends And Last Long
Solving a problem is an external motivation. You may move on after the problem is solved. However, if you can’t stop thinking about it and have fun exploring the numbers, this internal motivation could keep you in the data world even you don’t make any impact yet. I’ll talk more about this in the future posts.
More to come..
I hope the first article arouses your curiosity. Stay tune for the following posts.
🤩 I’m happy to hear how do you build product, what data do you check. Feel free to reach out to me on LinkedIn Karen Hsieh or Twitter @ijac_wei.
🙋🙋♀️ Welcome to Ask Me Anything.
