Salesforce Frequently Asked Questionslink
Read answers to frequently asked questions about the Fivetran Salesforce connector.
Which naming conventions does Fivetran use?link
Fivetran follows a set of standard naming conventions for schemas, tables, and columns. To learn more about our naming conventions, read the naming conventions section of our Core Concepts document.
Why is a particular table missing?link
There are some common reasons that you may not be able to find a Salesforce table that you're looking for:
- Fivetran cannot access the table because the connecting user does not have sufficient Salesforce permissions.
- The table is a "formula" or "compound" field.
- The table name is different from what you expected. Fivetran names the tables it delivers to your data warehouse based on the Salesforce "name" field for a given object. This is a field that an organization gives to the object, and it may differ from the display name or internal "label."
Note that we do not sync any pre-aggregated tables or views because you already have access to the underlying source tables. We also do not sync archived tables because of Salesforce's limitations.
Can I sync empty tables and columns?link
Fivetran can sync empty tables and columns for your Salesforce connector. For more information, see our Features documentation.
Who sets the system mod stamp?link
Fivetran doesn't set the system mod stamp for the Salesforce tables; these are established by Salesforce.
We begin syncing all tables at the same time, so generally, all of the tables are finished syncing at approximately the same time. Any variation is likely to result from some tables being bigger — thus taking longer to sync — than others.
To provide more insight into our process, we've also added a column into each table called fivetran_synced which displays the time at which that particular record was synced.
What happens when I change a field name in Salesforce?link
If you change a name that gets displayed in Salesforce reports it won't affect your connector.
However, if you change the name of the field itself, our system will:
- keep the old field
- add a new column, and
- backfill this new column with values from the old column, syncing updates to this new column from now on.
If you add a new column in the warehouse, any old values in that column will not get backfilled. In other words, if you hide permissions to a column and then grant permissions, Fivetran will only sync new records, not the old ones.
How can I change the precision of the DOUBLE data type?link
For DOUBLE data type values (for example, currency_field_type column data), we use the precision and scale from the SObject Describe API call to sync these values to the destination. You can increase the precision of the DOUBLE data type values from the Salesforce dashboard.
What happens if I add new columns or custom fields in Salesforce?link
For each account that you connect, we create a different schema in your data warehouse. The schema we create maps closely to the native Salesforce schema so that the data is in a familiar format for you to work with. If the structure of the data in the source changes (for example, you add new columns, custom fields, or change a data type) Fivetran automatically detects and pushes these changes into your data warehouse.
Why is a table not updated every sync?link
Not all tables are updated at every sync. When Fivetran finds that a table is not updated in the source for seven days in a row, we switch our strategy to checking that infrequently updated table for new data once a day. When the table is updated in the source again, we return to our usual update strategy.
Because we only check infrequently updated tables once a day, there can be a delay of up to one day when an infrequently updated table is updated in the source for the first time.
Another reason a table is not updated every sync is that it could be a re-import table.
Fivetran automatically detects tables with the replicateable = false value as re-import tables. We resync these tables because we can not capture deletes from them. These tables are included in the incremental sync but are re-imported in full at different frequencies.
The re-import frequency of the tables depends on how fast we can ingest data. Salesforce delivers data at varying frequencies and our speed of ingestion is completely dependent on them.
| Table Import Duration | Import Frequency |
|---|---|
| 3 seconds or less | Every sync |
| Between 3 seconds and 5 minutes | Twice a day |
| More than 5 minutes | Once a week |
We mark the re-imported tables as notRecommended in the dashboard and include a message that we will re-import them in full if they are selected. We exclude the tables from incremental syncs by default because they degrade performance. However, you can choose to include them.