Developer Tools

We at GoodData believe the analytics platform should provide the best possible developer experience. This starts by running an API-first analytics platform, but does not end there. We provide toolset that allows every developer to work with analytics as it would be code.

Why to treat analytics as code?

  • The code is easy to version. Imagine having every single iteration of your solution securely stored and revertible, and having a note to every change explaining why it was done, when, and by whom.
  • The code is easy to collaborate on. There are platforms dedicated to collaborative coding, like GitHub or GitLab, with features like Pull Requests and Code Reviews.
  • It is easy to automate an analytics solution or processes defined “as code”. It is not only about deployment but also quality control — test automation is a must-have in any modern software solution.

In short, it allows you to apply the best software engineering practices to analytics workflows. The API is the core of our developer tools but you can use Python SDKs, React SDK, and Visual Studio Code Extension.

Available Developer Tools

Python SDKs

The Python SDKs allow you interaction with GoodData with Python. With Python SDKs you can:

  • Retrieve datasets and metrics from your workspace
  • Retrieve and compute visualizations
  • Setup CI/CD pipelines
  • Test your visualizations

React SDK

The React SDK allows you create or embed visualizations and dashboards into your web applications. With React SDK, you can:

  • Display visualizations or existing visualizations from the GoodData using visual components
  • Create your new visual components to address your specific analytical needs
  • Retrieve data from the GoodData

VS Code Extension

GoodData for VS Code allows you to manage your analytics through code (YAML files) directly in Visual Studio Code. With VS Code Extension you can:

  • Retrieve analytical objects (metrics, datasets, visualizations and dashboards) from the GoodData
  • Create or update analytical objects in Visual Studio Code
  • Preview analytical objects in Visual Studio Code
  • Deploy analytical objects to a workspace
  • Setup CI/CD pipelines

Next Steps

  • Check Getting Started if you have not yet
  • Have fun, and apply the best software engineering practices to your analytics!