My current gig has reminded me how helpful it is to know your way around a database and to be able to use SQL to access and analyze data.
I may be a little biased because the first products I worked with when I got into IT had a significant data focus, including some quality time working on a data warehouse. All the same, having the ability to poke around a database and slice and dice data to answer questions can be very helpful.
There is probably some context where knowledge of SQL and an ability to work with data aren’t that important, but it seems as though there are fewer of those contexts.
With that in mind, I thought I’d share a few resources that further the case for you to learn SQL as well as some gentle introductions you can use as a starting point. I will tell you from experience that actually diving in and working with SQL is the best way to learn it.
SQL: The one technical skill all product people need to know
Will Lawrence believes If you want to use large amounts of data, you need to know how to use SQL. That said, you don’t need to be an expert in SQL. What’s important is that you know enough SQL to be able to extract, organize, and leverage the data necessary for your roles, be that as a business analyst, marketing manager, or product manager. In other words, you need to know “enough to be dangerous”.
Basic SQL skills for product managers
Thaisa Fernandes echoes Will’s sentiment and explains that data is a powerful tool for product managers. If you want to make use of that data, you’re going to have to work with databases, and that means you’ll probably want to have a working knowledge of SQL. Thaisa shares some of the basic things you need to know about SQL so that you can analyze data effectively.
SQL Skills for Product Managers
We’ve established that data is a powerful tool for product people. Richard Holmes goes so far as to explain that data to product managers is like ammunition to an assassin. While I’m not sure I’d use such a colorful metaphor, Richard has a point. Data, when handled properly, can help you make product decisions based on facts rather than opinions. Richard explains some key things that you need to know about SQL so that you can write queries, generate reports all without having to rely on others to get you every little piece of data.
Data Modeling for business analysts
In addition to knowing how to use SQL to extract and analyze data, it’s also helpful to know how to organize and structure it. Laura Brandenburg with Bridging The Gap put together a class on Data Modeling for Business Analysts (Affiliate Link) that includes core lessons covering all of the key data modeling techniques and the core concepts you need to know to successfully model data and build a shared understanding about your products data requirements. The course is very hands-on, and you’ll leave not just with theoretical knowledge but practical application creating these models in your own business or technical domain. You’ll learn 5 data modeling techniques: Glossary, Entity Relationship Diagram (ERD), Data Dictionary, System Context Diagram, and Data Map.
The Seven information smells of domain modelling
Another way to understand the data you’re working with is domain modeling, a great analysis tool that has many similarities to data modeling. Chris Matts and I described the seven information smells of domain modeling. These information smells are signals in your domain model that tell you there are more questions to ask. They indicate that you may not have a complete understanding of the information your domain cares about.
The smell could mean that you are missing information from our domain model or that you included incorrect information on the domain model. Focusing on the information smells leads you to the questions you need to ask which is a very fast process. When all of the information smells are gone or you decide the remaining ones are acceptable, you stop, which avoids analysis paralysis.