SQL and Python are the programming languages most commonly used by Data Scientists, but do Product Managers understand them? PMs from around the world took a stab at this dividing question. Read all about what they had to say.
Yes. Python is important.
Yes, SQL is important. In some companies, there is no specialist data analyst. Hence, you need to have basic idea of SQL so that you can retrieve and analyze required data.
Depends - I really like this question but I think there’s a bigger question buried here.
Really what I think we want to know is - “Should Product Managers build technical skills to access siloed data?”
I believe this largely depends on the maturity of your product’s BI infrastructure. If most of your data is accessible in a BI tool, it may reduce the need to build skills to get at siloed data for product analysis. At the end of the day, it’s important if:
As for what skills should be developed to enable this - thats a separate question. If you’re looking for the most transferable skillsets then probably Python & SQL. But if you want to drive value from your current product it would be best to consult your team to determine technology used (ex: Are you using a SQL DB or NoSQL db?).
Teach a person to fish
If you are just looking for insights into the data without getting too technical, you can look into Tableau and Power BI. SQL is always a good skill. Python less so for non-devs because there are often tools that will give you what you want without having to code.
This seems like it goes to how the PM's role is defined and varies depending upon the organization. Part of this is how much the PM is working direct vs how much the PM is guiding those who are working directly...
The more you have to ask other people for things, the slower you will go. If you want to iterate quickly on ideas then it's important to have the right tools at your fingertips. As a PM one of your most important tools is data and the subsequent analysis of that data. The more data you can get, the better. SQL is great for getting data, Python is great for analyzing it (but also Excel). I'd definitely learn SQL and then Excel or Python or something else for the analysis side.
Both? R or Python is ok
For those answering yes here can you please add the context of how mature your org is? That is really what determines the answer.
- <20 total employees. I think it could only be an asset, not a detriment regardless of size. I have seen larger companies with more robust BI capabilities, but often still have siloed data. I’m curious what your thoughts are on size (Smaller companies benefiting more from more technical expertise in product vs larger benefiting from it)?
100% not a detriment 🙂 The question though on whether PM's "need" SQL & Python is different. The challenge at bigger companies can often be even getting access to those DBs which store the data. E.g. at a large company (my org is 7000+) there is often a separate data analyst team that you partner with to get what you need in a more scalable manner. Less one-off queries, more re-usable and constantly refined analytics.
So I would answer the question ultimately as - yes SQL (not so much Python) is a must for smaller scale company PMs that won't have other resources to help with data analysis, but not a must for larger companies - though always helpful.
SQL is always a good skill to know.
Basic SQL is much needed
I got by with just understanding of code fundamentals for python… but I would say in todays age, BIG YES to SQL or at least an understanding of the difference between coding languages and QUERY languages. If you know one query language you can probably dink around in SQL but it saves SO much time going back and forth and not having to rely on your developers. Worth the time investment if you don’t know it now.
Product Managers could be asked and expected to wear almost any hat depending on the situation, company or industry
I am not sure if the company size alone can determine whether PM would need SQL or not. My previous company had approx 5000 employees. Products were from 7 to 10 years ago in the market, hence can be considered mature company. But there were still no data analyst team and PM needed SQL. So I think it depends whether company has separate data team or not. Large companies has higher probability of having data teams and startups has lower probability of the same. But it can not be taken as rule of thumb as there are lots of exceptions. The best way to clarify it by asking a PM working at the company before applying (what skills are required). And yes, it is a skill worth investing your time.
My former life was as an ETL developer, so plenty of SQL skills to say the least :) However that has been one of the least necessary skills in my product management career. Again, never a detriment, but there are generally higher impact areas as a PM to focus on, and hire people to handle.