One such gem came with the introduction of Jupyter Notebooks within Azure Data Studio.
Notebooks are not a new concept, they have been commonplace in academic circles for years, and first came to my attention when working with Python.
Notebooks offer a new way of sharing information. Allowing you to encapsulate executable code, data, and formatted narrative in the same document. The original use case was to exchange analytical findings, but I have found them useful for the following purposes:
Interactive tutorials – Allowing the learner to try the methods they are learning about without having to switch applications.
Troubleshooting guides – Providing support users with not only investigatory code to run, but also explanations as to how the results should be interpreted and responded to.
Repeatable test plans – Standard test scripts which can be executed, and the results saved within the document for future review and audit purposes.
If you would like to see examples; I have begun uploading notebooks versions of some of my old blog posts, allowing a level of interaction not previously available on my website.
Blog Notebooks
More information on notebooks can be found here.