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Exploring our Sample Dataset

We had yet to find a sample dataset that reflected data found in a B2B SaaS startup. So we made this publicly accessible database to run against our SQL templates.

Our fake startup

This PostgreSQL database is for a fake B2B SaaS company called Marker. It's a tool that makes it easy for remote teams to whiteboard. Think: Mural, Miro, or Figma.

Tables in our fake database

The users table is populated with ~800 users. All names and emails are fictitious. Any resemblance to actual persons, living or dead is purely coincidental.

The teams table is populated with ~160 teams. Again, all teams are fictitious (although we tried to give the names a startup feel). Note: all teams have users, but not all users have teams (i.e. some people use Marker on "single-player mode").

The events table captures ~20,000 analytics events. With this data set, you can analyze an onboarding funnel, a feature launch, and much more. Here are the distinct event names:

The tickets table is populated with ~70 tickets. What this table lacks in size it makes up for in realism. With data in this table you can detect spikes in issues or use Linear Regression to see which sub-metric correlates most strongly with CSAT.

The nps_responses table is populated with ~2000 responses. It's perfect for analysis on NPS (and our NPS analysis template is arguably the most straight-forward one on the web).

Coming soon:
We plan to add tables for transactions, subscriptions, and webhooks (a join table to connect to fake Stripe and Clearbit data).

Accessing this database

In PopSQL, create a new connection and use the credentials below:

Nickname Sample Data - Marker
Type PostgreSQL
Port 5432
Database marker
Username demo
Password demo

Tools we found useful in making a fake DB

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