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March ’23 Updates: Verify and Merge in Salesforce; Tagging and more

By March 23, 2023April 4th, 2023No Comments

Our second release of 2023 is chock-full of new goodies. We are introducing a new Lightning component that runs verifications directly in Salesforce, and we have added Merge capability to our existing duplicates component. In addition, this release includes a new tagging feature for Trimmr. 

Read on to discover the highlights and, as always, you can find a detailed list of all our updates and fixes on the DataGroomr Support Portal.   

Keep in mind that many of the updates we made were driven by requests submitted to the Ideas Exchange portal. So keep them coming.

Components and More Components

Merge Records Inside Salesforce

Last year, we introduced a companion component for DataGroomr that allows users to view duplicates directly in Salesforce. Our customers loved this feature, but they also asked if we could extend the functionality to enable users to perform merges as well. This month’s update does just that. 

DataGroomr Administrators can assign Merge Enabled users using the Manage Users page. 

Users with this privilege will be able to view duplicates and run merges by pressing the available Merge button. Users without access will still be able to view, but not merge. 

Verify Phone, Email and Mailing Addresses Directly in Salesforce

Another common request that we have received is to allow users to run verifications directly in Salesforce. This month, we are releasing an app with that functionality. You can see it in action below. 

The app will soon be available for installation directly from the AppExchange or can be installed right now from our website. 

Trimmr Enhancements

Tagging Groups

We are excited to add the ability to tag matched groups in Trimmr. This functionality is particularly useful for categorizing data for review or merging at a later time. Users can press the tag icon located in the upper left-hand corner of the window to select existing tags or add new ones.   

Once tagged, matched groups can be retrieved using the Search window. 
 

Type-ahead filter for dropdown fields

Users can now quickly find desired values by typing inside dropdown fields. Previously, users had to scroll to select a value. 

Supervisr Enhancements

Group datasets by module when assigning matching model 

Users have always been able to assign matching models directly from the Matching Models window, but with a large number of datasets, this could be complicated. To simplify this task, datasets are now grouped by module. 

Schedulr Enhancement

Reports for Mass Verification Jobs 

Scheduled Mass Verifications jobs now include an email field. A report will be generated after the job completes and sent to any email addresses added there.  

What’s Coming in the Next Release?

We are planning to add an ability to stop Mass Merges and other bulk jobs. Users have requested an ability to pause or terminate these tasks for a variety of practical reasons. 

On a more exciting note, you have probably heard the recent announcements regarding AI-powered bots. We are working on our own implementation of this technology. We hope to have a major announcement in the near future!

Please follow these release announcements to stay tuned and, as always, we appreciate your feedback. If there are other features that are important to you, we invite you to submit them to the Ideas Exchange portal or vote on existing features already there. 

As always, we would like to remind you that we offer a free 14-day trial of DataGroomr. Please feel free to forward this article to your Trailblazer colleagues. They can start the Free Trial by logging in with their Salesforce credentials. There is no setup required, and you can get a handle on the duplicate management of your data right away! 

Happy DataGrooming, Trailblazers! 

Ben Novoselsky

Ben Novoselsky, DataGroomr CTO, is a hands-on software architect involved in the design and implementation of distributed systems, with over 19 years of experience. He is the author of multiple publications about the design of the distributed databases. Ben holds a Ph.D. in Computer Science from St. Petersburg State University.