Data Science Apps for Plug and Play Data Science

I was reading the 12 factor App and was struck by how much data science practitioners could use these principles too, for example when making a Shiny Dashboard App

Also I hope we can have more plug and play data science for mobile data or data generated by mobile apps (which is increasing)

Screenshot from 2016-05-11 23:11:17

An example is this app here https://gallery.shinyapps.io/CampaignPlanner_v3/ which can possible modified to add integration with Google Web Analytics API (etc).

This approach can make R more enterprise ready for production environments where it currently lags behind Python in terms of both appeal as well as trained people.

http://12factor.net/

The Twelve Factors

I. Codebase

One codebase tracked in revision control, many deploys

II. Dependencies

Explicitly declare and isolate dependencies

III. Config

Store config in the environment

IV. Backing services

Treat backing services as attached resources

V. Build, release, run

Strictly separate build and run stages

VI. Processes

Execute the app as one or more stateless processes

VII. Port binding

Export services via port binding

VIII. Concurrency

Scale out via the process model

IX. Disposability

Maximize robustness with fast startup and graceful shutdown

X. Dev/prod parity

Keep development, staging, and production as similar as possible

XI. Logs

Treat logs as event streams

XII. Admin processes

Run admin/management tasks as one-off processes

Author: Ajay Ohri

http://about.me/ajayohri

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