One of the best low effort, high return tweaks that you can do for your analytics project is to set up a standard folder structure across all your projects and teams.

I tend to use directory structure from Python package kedro but any good similar structure would work as well. Here’s the structure of the kedro project.

    project-dir         # Parent directory of the template
    ├── .gitignore      # Prevents staging of unnecessary files to `git`
    ├── conf            # Project configuration files
    ├── data            # Local project data (not committed to git)
    ├── docs            # Project documentation
    ├── logs            # Project output logs (not committed to git)
    ├── notebooks       # Project-related Jupyter notebooks 
    ├── pyproject.toml  # Identifies the project root and contains
    |                   # configuration information
    ├── README.md       # Project README
    ├── setup.cfg       # Configuration options for `pytest` when doing 
    |                   # `kedro test` and for the `isort` utility when 
    |                   #  doing `kedro lint`
    └── src             # Project source code

Standard directory structure has the following advantages:

• Efficiency. An organized directory structure accelerates the development process by minimizing the time spent searching for specific files or resources.

• Readability and maintainability: A logical and clear structure makes it easier for team members to understand the project’s layout, components, and how they interact.

• Standardisation. By adopting the same folder structure across all the projects, makes it easier to navigate new or old project for all team members.

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