Software Alternatives & Reviews

Number Analytics

It is a cloud based statistical software for beginners and business users.

Number Analytics Alternatives [Page 3]

The best Number Analytics alternatives based on verified products, community votes, reviews and other factors.
Latest update:

  1. 18

    Cnvrg.io is a full-stack AI data science platform that makes it easy for data scientists of all levels to manage data, train models, collaborate, deploy AI applications, and create AI applications.

    Open Source

  2. 20

    Solvuu is a web-based data science platform that enables scientists to easily manage, analyze, explore, visualize and share genomics data.

  3. The PAQATO After-Sales Experience Platform is the growth driver that makes online stores successful for tomorrow.

    Visit website paid €349.0 / Monthly

  4. 17

    NumXL is a Microsoft Excel time series software add-in.

  5. 18

    Analance is an advanced analytics platform with tools to capture, integrate, visualize and analyze data.

  6. 19

    Knoldus is a data engineering and analytics platform that helps you build intelligent applications at scale.

  7. 16

    SHAZAM is a comprehensive computer program for econometricians, statisticians, biometricians, sociometricians, psychometricians, politicometricians and others who use statistical techniques.

  8. 50

    JASP, a low fat alternative to SPSS, a delicious alternative to R.

    Open Source

  9. 17

    Mass Analysis data importing, display integration, background subtraction, display of extracted chromatograms, molecule match...

  10. 45

    RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

  11. 16
  12. 17

    Equip data scientists with self-service access to any data, anywhere, so they can quickly develop and prototype machine learning projects and easily deploy them to production.

  13. 17

    Low cost statistical software

  14. 19

    dotData is a data automation platform that enables enterprises to operationalize data science and machine learning.

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