Once a dataset is released, you can return to it to make changes at any time. Changes to datasets are tracked in Redivis as versions. Anyone with access can view and work with any version of the dataset.
How to work with versions when updating a dataset:
Edits to the data itself or table names will need to be released as a new version before anyone can see them.
Edits to the dataset information, table information, or variable metadata can be made on the current version and will be live as soon as it's saved. Or if you would like to preserve the existing dataset as it is, you can create a new version and make updates to that instead. No one will be able to see these updates until the new version is released.
Edits to the dataset name and access configuration (and for administrators only - published status) will always affect all versions.
All data within a dataset is encapsulated in discrete, immutable versions. Every part of the dataset except for the name, access setting, and published status is versioned. All tables in a dataset are versioned together.
The first version of this dataset was created automatically for you. Once that is released, you can choose to create a new version at any time by clicking on the version dropdown menu and selecting "Create new version"
Once you've created a new version you can make changes by returning to the tables list and clicking the "Edit data" button. This will take you into the data editing interface where you can upload new data and/or change existing data.
Subsequent versions will always build on the previous version. However, you may choose to completely overwrite the existing content by replacing your current version with new uploaded data.
You can upload additional data to this table in subsequent versions with "append" or "replace" blocks in the edit process which follow the same upload format.
Redivis computes row-level diffs for each version, efficiently storing the complete version history in one master table. This allows you to regularly release new versions and maintain a robust version history without ballooning storage costs.
After a time, the tables associated with historic versions will automatically be archived. Archived tables can still be used and queried just like any other table, with the sole limitation being that the cell preview is not available on archived tables.