Google Sheets Advanced Settings

For users who have some experience working with their data in Panoply, there are a number of items that can be customized for this data source.

For users who have some experience working with their data in Panoply, there are a number of items that can be customized for this data source.

1. Destination Schema:This is the name of the target schema to save the data. The default schema for data warehouses built on Google BigQuery is panoply. The default schema for data warehouses built on Amazon Redshift is public. This cannot be changed once a source has been collected.
2. Destination: Panoply selects a default destination. These are the tables where data is stored.
   • The default naming convention is sheets_<filename>_<sheetname>. For example if you had a spread sheet named "App Install Metrics" and it contained a sheet (tab) named "app_installs", it would be stored in Panoply as sheets_app_install_metrics_app_installs. 
   • To prefix all table names with your own prefix, use this syntax: prefix_<__tablename>, where prefix is your desired prefix name and <__table_name> is a variable that represents the <filename>_<sheetname>.
3. **Primary Key: **Users can define which column contains the table's Primary Key. If this option is left blank and the sheet does not contain an ID column, Panoply will insert an id, formatted as a GUID, such as 2cd570d1-a11d-4593-9d29-9e2488f0ccc2.
4. Exclude: The Exclude option allows you to exclude certain data, such as names, addresses, or other personally identifiable information. Enter the column names of the data to exclude.
5. Parse String: If the data to be collected contains JSON, include the JSON text attributes to be parsed.
6. Truncate: Truncate deletes all the current data stored in the destination tables, but not the tables themselves. Afterwards Panoply will recollect all the available data for this data source.
7. Click Save Changes then click Collect.
   • The data source appears grayed out while the collection runs.
   • You may add additional data sources while this collection runs.
   • You can monitor this collection from the Jobs page or the Data Sources page.
   • After a successful collection, navigate to the Tables page to review the data results.