The fastest way from data to insight ...

Process and analyze heterogeneous, evolving or poorly structured data in a heartbeat  

Share tools and workflows with users whose data is only similar to yours. There´s no need to share a server  

Get up and running quickly - user-friendliness and easy customization cuts implementation time and total cost of ownership  

Easy to use

!nstead of focusing on a data pipeline, we let you work with your data and see it change as you add (and sometimes undo) logic – inventing your workflow as you go along. No coding skills are necessary. As soon as you give your work a name, Quantitative Commons records any action into a repeatable, sharable and editable workflow.

Joining, merging or nesting multiple data sources and mapping to external storage solutions by simple drag-and-drop makes Quantitative Commons the tool of choice when data is rowdy and data scientists are scarce.

Knows what to do with your data

As soon as you start recording your actions, Quantitative Commons remembers the structure of your data, letting it suggest or automatically run the appropriate workflow the next time such data is encountered. Using advanced classification algorithms, Quantitative Commons can even recognize and process data that is only similar to, or of the same type as something previously encountered, making it easy to manage large numbers of disparate and evolving data sources while increasing the scope for collaboration.

Adapts to your needs

While Quantitative Commons comes with some 150 tools out of the box to extract, clean, prep, transform, merge, join, analyze, visualize, export and load data, it is really a platform more than a static piece of software. You may script your own tools using python or C# - even the user controls for your custom functionality are defined in code, or you may have us make a custom version for you. Or, if you like, you can acquire a copy of our C# tool library to develop your own custom version of Quantitative Commons, and share it with whomever you want to collaborate with.

!ntroduction (1 min)

Sales data example case (10 min)

Health data example case (6 min)

Communication data example case (17 min)