The world of data is changing. No longer only the domain of data analysts, anyone with the right tools and some SQL skills can get started exploring data.
Tools like PopSQL empower product managers, marketing, and customer success teams to not just interpret the story behind the numbers but share results quickly and easily.
This is a sponsored post - PopSQL contacted me and asked if I'd be interested in reviewing their collaborative SQL editor, and provided access for me to test it out. That said, these are my impressions and opinions.
If you’ve never used a tool like this before you may be wondering - what is a collaborative SQL editor, and why do I need one?
Code editors, even those designed with data analysts in mind, are nothing new. But being able to share both the code and the results quickly is a game-changer.
In this post, I’m going to explore a dataset I’ve never used before, write some code, create a dashboard, and test out the PopSQL team’s favorite features.
To use PopSQL you’ll need to sign up for a free trial. After this, there are instructions on how to connect to your database to start querying.
Like other tools, getting up and running with PopSQL is as simple as providing your database connection details. This makes getting started accessible for data professionals and business users alike. All the popular database types are supported with language guides available if you need an extra helping hand.
When I took the PopSQL browser-based tool for a spin I used the RNAcentral public database. I’m not an expert in this kind of data, but I might be soon!
This is where the fun starts. I haven’t used this database before so I used a recommended query from the RNAcentral team. It turns out this is a long-running query with just one of the tables being 58M rows.
Lucky for me there are some guardrails put up in the PopSQL editor which limit the results to 100 rows. This is great for those who are just getting started with SQL, and folks like me who should know better and just forget to add a LIMIT.
Queries can be shared, scheduled, and added to by teammates from here. Not all tools come with a job agent or scheduler out-of-the-box so I’m a big fan of this feature.
The results editor is more than just a grid. Rather than exporting the data and adding it to a BI tool or Excel, there’s an option to see a chart.
Part of the reason data projects run slowly is the back-and-forth with our stakeholders as we learn more about the data. These projects are delivered faster when you can mock up a dashboard quickly for the stakeholder. They can ask questions earlier, add their thoughts on what else they would like to see next, and the project is delivered on time. This is probably my favourite feature for data exploration on the fly, rather than scrolling around a grid or shuffling data between tools.
Everyone loves a good dashboard, right?
To add a chart to a dashboard you need to have a SQL query ready and saved. If you or your colleagues have ever used Salesforce, it’s very similar to creating a report first then adding it to your dashboard.
Visualization-heavy BI tools like Tableau have more robust charting. PopSQL gives you the same look-and-feel of Google Sheets, but with the added functionality of scheduling. For teams who don’t work in data every day the charts will look familiar right down to the color scheme. The PopSQL team informs me that more features for charts are on the roadmap: custom colors, more chart types, embeddable charts, and more.
Another great feature is the option to share dashboards and queries with others. Those invited into a team can see an editable version or a slick presentation version - great for those management meetings where you want everything fixed in place.
Overall, I am pretty impressed with what I’ve seen in the PopSQL browser-based tool. I like that it’s quick to get started, I can run queries and share them, visualise results as I go, and present results in dashboards.
What I’d like to see next are more chart types or integrations to do so, the option to add a secondary axis, and custom colors for charts.
If you’d like to see a demo in action and read more check out the links below: