Resources about the purpose and the importance of a data science platform for businesses, including examples of various platforms like Continuum Analytics, Adatao and more.
Table of Contents:
Below we have compiled publicly available sources from around the world that present views on Data Science Platforms.

Learn More About Popular Data Science Platforms

Perspectives on Data Science Platforms

Specific Environments


Further Reading

  • Arimo - AdataoResources about Arimo (formerly known as Adatao), a company that offers an interface that enables business users, data scientists, developers, and data engineers to collaborate and present insights from big data.
  • AlgorithmiaResources about Algorithmia, a company that provides a marketplace that enables algorithm developer to explore, create, and share algorithms as a web services.
  • Context RelevantResources about Context Relevant, a big data analytics startup that sells on-premises software, cloud services, and professional service solutions to help businesses accelerate analysis and actionable insight.
  • Continuum AnalyticsResources about Continuum Analytics, the creator and driving force behind Anaconda, the leading Open Data Science platform powered by Python.
  • DataikuResources about Dataiku, a company that develops collaborative data science software marketed for big data.
  • Domino Data LabResources about Domino Data Lab, a company that provides data science teams with best practice knowledge management, reproducibility,rapid development and deployment of models.
  • Mode AnalyticsResources about Mode Analytics,  a cloud service that data analysts can use to query and visualize data.
  • PlotlyResources about Plotly, a service for creating and sharing data visualizations that also offers statistical analysis tools and a robust API with the ability to graph custom functions and a built-in Python shell.
  • NutonianResources about Nutonian, a data mining software package. It offers Eureqa Desktop, a technology solution that uncovers the intrinsic relationships hidden within complex data in oil and gas, life sciences, and retail industries.
  • YhatResources about Yhat, a cloud solution that allows users to embed predictive models written in Python and R into various software applications.


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