Below is the answer and explanation for the question in the Salesforce Exams.

• Modify dataflows to exclude unused fields and include a filter to extract relevant data.
• Start over again with new dataflows that exclude unused fields with a filter to extract relevant data.
• Update the existing data sync (replication) process by removing unused fields with a filter to extract relevant data. ✅
• Scale down the number of datasets to help improve data sync (replication) performance.

Correct Answers

Update the existing data sync (replication) process by removing unused fields with a filter to extract relevant data. ✅

Explanation

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
With CRM Analytics, you can schedule sync to run automatically, manually run a sync, and monitor a sync’s progress, all in the data manager.
Verify the Incremental Sync Settings 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.

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