This dashboard offers users an overview of each of the 4 datasets exposed by Keypup:
When users connect their Git repositories or Project management projects, Keypup takes care of fetching and normalizing third-party data.
Data is populated into corresponding datasets based on their type (e.g. data originating from reviews will feed the “Reviews from pull requests” dataset), and each record is augmented with metadata and correlated data (e.g. first_commit_at field on pull requests).
The data exploration dashboard is a great way to understand the Keypup taxonomy by looking at concrete examples of values retrieved from your apps and mapped by Keypup. It is also a good starting point to understand how reports and insight are built.
The reports of the exploration dashboard focus on the most important and common fields but the list is by no means exhaustive. A complete list of all available fields can be found here.
Insights
"Issues" Dataset Exploration: This report is an entry point to understand what issue data is imported from the connected project management and Git sources. Users use this report to understand how data is mapped and populated into the dataset.
"Pull Requests" Dataset Exploration: This report is an entry point for understanding what pull request data is imported from the connected Git sources. Users use this report to understand how data is normalized and populated into the dataset.
"Commits from pull requests" Dataset Exploration: This report is an entry point for understanding what commit data is imported from the connected Git sources. Users use this report to understand how data is normalized and populated into the dataset.
"Reviews from pull requests" Dataset Exploration: This report is an entry point for understanding what review data is imported from the connected Git sources. Users use this report to understand how data is normalized and populated into the dataset.
"Comments from issues, pull requests and reviews" Dataset Exploration: This report is an entry point for understanding what comment data is imported from the connected Git and project management sources. Users use this report to understand how data is normalized and populated into the dataset.