I love that Count is flexible and easy to understand, especially for someone like me who is not an engineer. The canvas layout is visually helpful, which makes it really nice to work with. The team's great and very helpful, which I really appreciate. Most BI tools are unusable for someone like myself, but Count allows me to understand data without relying on others. The initial setup was very easy.

That I can look at visualisations but then easily jump into the underlying data in an understand way as a layman. The AI functionality is also helpful, it shows its workings and the data can be reviewed the same way as mentioned above.

I have switched to Count for all the analysis I run, so I would say I use it on a daily-basis. With Count, you can have queries, plots, text, reports, and comments all in the same place. I find this extremely valuable, as it effectively makes everything self-documenting: the queries that support the results, the interpretation, and the reviews that were made all live together. Moreover, we can collaborate in real-time on the same canvas, which is amazing. I really like that Count allows you to create tiles and reference results, in a way that feels similar to a DAG in dbt. This helps avoid a lot of code duplication and significantly streamlines query creation. Personally, I think this makes a big difference because it allows me to split complex queries into clearly defined components and then combine their results as needed. When using other tools, I sometimes felt constrained by the lack of flexible filtering, which was often managed at the organization level and pushed me toward hacky solutions. With Count, control cells make it easy to implement the exact filters you need, giving you a lot of freedom and power to build very flexible dashboards. Finally, I think the Count support team is excellent. They are consistently helpful, whether I’m stuck or just looking for best practices to implement something in the tool. They either provide a solution or take note of the feedback to improve the product. A good example is the recent addition of support for different scales in facet plots, which addressed a limitation I personally encountered.