Deployment

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Deployment#

  • The term deployment can have various meaning, e.g.,

    • The phase of a data science project where one scales up to full production, possibly with a release to the public.

    • The action of moving a pipeline from development to usage, maybe including going from personal computers to external (paid) servers.

    • Or, in our case, wrapping all the API calls, database tables, functions and logic in a way that makes it accessible to users in an intuitive way.

      • Dashboard

      • Report

      • Web app

  • Together with the software, there may be documentation, training, policies, restrictions, etc.

DDDM revisited#

  • We started with the following points:

    1. Know your objectives

    2. Find relevant data

    3. Pre-process data

    4. Analyse data

    5. Make decisions

  • Before we start working on points 2.,3. and 4., we will have a brief introduction to dashboards.

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