What I like most about Count is its ability to combine SQL, Python, and interactive data storytelling in a single collaborative workspace. It makes it easy to explore data, build visualizations, and present insights without constantly switching between different tools. Collaborative notebooks that allow teams to work on analyses together in real time. Support for both SQL and Python, providing flexibility for different types of data workflows. Interactive visualizations that update automatically as the underlying data changes. Clean, intuitive interface that encourages exploratory data analysis. Easy sharing of reports and dashboards with stakeholders. For me, the most valuable feature is the live, collaborative notebooks. They make it simple to iterate on analyses, receive feedback, and keep everyone working from the same source of truth. The biggest benefit is increased productivity. Count streamlines the journey from querying data to creating interactive reports, helping teams collaborate more effectively and deliver insights faster.

I like that it’s a very flexible collaboration and analysis tool. It solves a lot of the headaches that come with working alongside other analysts, and it also makes it easier to share those analyses with business stakeholders. On top of that, its LLM integration is solid and pushes the overall user-friendliness even further. It integrates well with our data warehouse (BigQuery), and is generally quite performant. It's very useful that you can both run SQL and Python for analysis. The support team is very helpful.

I like Count for its versatility, allowing quick iteration of analysis that requires non-standard data sources and blends between data from different sources. It lets me define sources, calculations, aggregations, etc., on the fly more intuitively than many other tools.