Considerations for Scheduling Data.com Clean Jobs | Salesforce
Considerations for Scheduling Data.com Clean Jobs
Review considerations for scheduling your records to be cleaned automatically using Clean jobs.
Available in: Salesforce Classic
Available with a Data.com Clean license in: Professional, Enterprise, Performance, and Unlimited Editions
If you have set up triggers to run when account, contact, or lead records are updated, and your triggers perform SOQL queries, the queries may interfere with jobs for those objects. Your Apex triggers (combined) can’t exceed 200 SOQL queries per batch. If they do, your job for that object will fail. In addition, if your triggers are @future methods, they are subject to a limit of 10 @future calls per batch.
Jobs are only available to organizations with a Data.com Clean license.
You must have jobs scheduled for at least one day in a week them to run.
Jobs only process records of enabled objects
In a full sync job, all records are cleaned, regardless of their clean status. In an incremental sync job, only records with a Not Compared clean status are cleaned.
When a full sync job runs, it runs instead of an incremental sync job.
If a full sync job is scheduled to run, it runs even if no records have changed.
The duration between jobs is counted from the time the previous job finishes to the start of the next job.
Jobs are queued according to your scheduling settings, and they run independently for accounts, contacts, and leads. If you use Data.com Social Key, jobs also run a process that finds and associates social handles for your contacts and leads.
How long it takes for a job to complete depends on several things, including which matching service you’ve selected (for account jobs), how many records your job cleans, and overall Salesforce performance. Using Data.com matching, it takes about a day for jobs to clean 3,000,000 records. Using DUNSRight™ matching, it takes about a day for jobs to clean 750,000 records.
Use your sandbox environment to try out the automated clean jobs before running them in your production org with live data. After Data.com Clean is provisioned in your production org, refresh your sandbox so it has the same permissions and data. Then follow the steps in Implementing Data.com Clean to set up Clean in your sandbox. If everything runs smoothly in your sandbox environment, follow the same implementation steps in your production org.
Jobs scheduled in a sandbox environment expire after 30 days.
For best results, we recommend including a valid value for the Country and State/Province fields.
Before scheduling jobs, we recommend you schedule regular backups of your account, contact, and lead data. It’s always a good practice, and if your Salesforce records are ever matched inappropriately, you can revert to previous versions.
Set up field history tracking for accounts, contacts, and leads. Field history tracking helps you identify changes to field values, and tracks who made changes and when. If you use field history tracking, make sure you add the Account History, Contact History, and Lead History related lists to those objects’ respective page layouts.