How is Count different from other data notebooks?

  1. Count is designed for SQL. This is not a Python notebook, which means writing SQL isn’t an added feature, it is incorporated into all aspects of the tool (e.g. intelligent auto-complete, visualization framework build on SQL)
  2. Built for big data. Because Count runs directly on your database, you do not have to spin up a server or worry about your local machine running out of memory. This makes it ideal for analyzing large datasets, where you can take advantage of database optimization and caching. 
  3. Powerful Built-in visualization. In Python-based notebooks, the user has to learn a complex visualization library to visualize data. Or there is a simple query builder that makes it easy to do quick bar and line charts. Count’s visual builder is far more powerful than standard drag and drop visual builders, and doesn’t require any bespoke coding language. 

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Taylor Brownlow's profile on astorik

Taylor Brownlow

Head of Data
Head of Data at Count

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