You can review the imported datasets that you own or have been shared with you.
NOTE: If the data underlying the imported dataset is not available, the imported dataset is still listed in the Library page, since it is just a reference to the data.
Tip: To create an imported dataset, click Import Data. For more information, see Import Data Page.
You can filter the imported datasets based on the ownership of the datasets. Columns:
- Name: Name of the imported dataset.
- Owner: Owner of the imported dataset.
- In Flows: Count of flows in which the imported dataset is in use.
- Source: Flow or datastore where the imported dataset is located.
- Last Updated: Timestamp of the last time that the imported dataset was modified.
- Browse: If displayed, use the page browsing controls to explore the available objects.
- Search: To search object names, enter a string in the search bar. Results are highlighted immediately in the Library page.
- Sort: Click a column header to sort the display by the column's entries.
Context menu options:
NOTE: The context menu options vary based on the ownership of the datasets.
Preview: Inspect a preview of the dataset.
NOTE: Preview is not available for binary format sources.
- Use in new Flow: (Imported dataset only) You can create a new flow and begin immediately wrangling the dataset. This step also creates a recipe in the flow.
- Add to Flow: Add the dataset to a new or existing flow.
Make a copy: Create a copy of the imported dataset. This option is not available for reference datasets.
Edit name and description: Change the name and description of the dataset.
- Remove Structure: Removes the structure of the dataset and converts into a raw dataset.
Refresh Dataset: If available, this option refreshes the dataset's metadata with the latest source schema. For more information, see Overview of Schema Management.
NOTE: If you attempt to refresh the schema of a parameterized dataset based on a set of files, only the schema for the first file is checked for changes. If changes are detected, the other files are contain those changes as well. This can lead to changes being assumed or undetected in later files and potential data corruption in the flow.
Delete Dataset: Delete the dataset.
Deleting a dataset cannot be undone.
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