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R for Big Data in One Picture


This picture covers the following topics:

  1. Basic stack

  2. Integrated platforms

  3. Visualization

  4. Data formats

  5. Large & out-of-memory data

  6. Hadoop

  7. Glue

  8. As backend

  9. GPU

  10. in-database analytics

  11. Parallel

  12. Efficiency

  13. Packages

Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed in http://www.datasciencecentral.com/profiles/blogs/r-for-big-data-in-one-picture

 
 

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Disclaimer: The products and solutions presented on this website are at different stages of development, ranging from conceptualization and research to experimental phases, pilot programs with educational institutions, and full-scale production deployments. Analytikus continuously works on the evolution and enhancement of its technologies, meaning that some features may still be under development or adaptation to meet the needs of the education sector.

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