Use data sync to pull data to CRM Analytics on a regular schedule. By scheduling sync from Salesforce and remote systems ahead of time, your recipes have less to do and run faster. To lighten the load even more, CRM Analytics can sync supported local Salesforce data incrementally by default, meaning that only data that’s changed gets synced.
Use Data Sync with Recipes
Recipes can use data previously synced to CRM Analytics or unsynced, direct data. For help understanding when to use data sync or direct data, see Pull Data Directly into Recipes. To expand the synced data available when you build and run a recipe, add objects and fields to data sync.
Schedule your recipe data objects for incremental syncs, periodic full syncs, and full syncs. Incremental syncs run faster because they extract only the latest changes to the Salesforce object. Changes to the datasets and Salesforce objects always trigger a full sync to keep your data accurate. For more information, see Configure Incremental Sync for Salesforce Data.
Use Data Sync with Dataflows
Data sync makes your dataflow runs faster. Without data sync, a dataflow performs a separate extract each time it needs data from a Salesforce object. Let’s look at an example. Imagine your organization has three dataflows, extracting data from Salesforce objects as follows:
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| Sales Analytics App Dataflow |
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Every time these dataflows run, they must extract all this Salesforce data. And the more data there is, the longer the dataflow takes to run. In addition, the dataflows perform separate, duplicate, extracts from the same object. For example, all three dataflows extract Accounts data.
With data sync, all of these extracts are performed as a separate process, which you can schedule to take place before your dataflows run.
| Accounts | Contacts | Opportunities | Campaigns | Leads | Cases | Users | |
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This synced data is then available to all your dataflows, which run faster because they no longer have to extract any data—just load and transform.
- Add, Remove, and Manage the Objects and Fields That Sync to CRM Analytics
As your analytics and business needs change, the data synced to CRM Analytics change, too. Add, remove, and change the settings for the objects and fields included in data sync. - Schedule, Run, and Monitor Data Sync
In CRM Analytics, you can schedule sync to run automatically, manually run a sync, and monitor a sync's progress, all in the data manager. - Configure Incremental Sync for Salesforce Data
Before you run or schedule data sync, specify whether the sync extracts incremental changes or all records from each Salesforce object. By default, CRM Analytics performs an incremental sync. An incremental sync runs faster because it extracts only the latest changes to the Salesforce object. - Enable Data Sync and Connections
Data Sync is enabled by default if you turned on CRM Analytics after the Winter ’20 release. If you turned on CRM Analytics before the Winter ’20 release, manually enable Data Sync and Connections to optimize your dataflows and connect to external data. - Sync Out for Snowflake
Sync Out for Snowflake exports your raw local Salesforce data via CRM Analytics to Snowflake using the CRM Analytics output connector for Snowflake. With Sync Out for Snowflake, keep your Salesforce data in Snowflake up to date using scheduled Data Sync without the need for a third-party ETL tool. Fresh Salesforce data is vital if you maintain a central Snowflake data lake for processing, analysis, business automation, or storage. For example, give your shipping logistics team the freshest data by merging your account data from your system of record, Salesforce, with your ERP’s shipping data in your data lake. - Data Sync Limits and Considerations
Here are some things to consider when you’re working with data sync.