Count

Count

A collaborative data analysis platform built around notebooks.

Teams

Count

caters to:

Data
Marketing
Product

What need does

Count

fulfill?

Count enables data teams to find and share insights quickly, supercharging decision-making across their organisation. It provides a seamless workflow for SQL analysis, letting data teams explore their data in a reactive SQL notebook, collaborate in real-time and publish their results as beautiful, interactive data apps that their whole organisation can use.

What are the core features of

Count

?

  • Collaborative notebooks: Build analysis together and share code all in the same live document.
  • Cell-referencing: In count, every query is a cell. And you can reference any other cell in your queries. This let’s you build your analysis step-by-step, paramertize your analysis to make it interactive, or better add validation steps. 
  • Built-in Visuals: The Count visual builder makes it easy to build complex visualizations without having to learn a complex coding library. 
  • Interactive Control Cells: You can make your notebooks interactive by creating control cells. These cells can be linked into your analysis seamlessly so your readers can filter, search, order, or just say hello.

What are the benefits of using

Count

?

  • An improved SQL workflow for analysts: Count’s collaborative notebook interface provides a faster, more natural approach to SQL analysis, allowing you to build your analysis step-by-step and do it in real-time with others in your team. The built-in, high-quality visuals mean you can go straight from data to presentation in one place without sacrificing quality. 
  • Reports over dashboards. Dashboards can be great for operational metrics, but for anything requiring communication of context, they are far less effective. Building reports in Count means you can always keep your analysis in context and improve decision-making across the organization.
  • Works with big data. Count runs directly on your database, and your data stays exactly where it should, in your database. Unlike typical python-based notebooks, it is ideal for analyzing big data and allows you to leverage the full power and speed of your data warehouse.
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