DataGroomr Support

Salesforce Deduplication Minus the Frustration DataGroomr is a comprehensive deduplication tool for cleaning your Salesforce data that is powered by machine learning. This tutorial gives you a quick overview of DataGroomr UI and functionality, introducing you to the new virtual data scientist that is going to h...

In this video, our Solution Expert, Sarah demonstrates how to use Dashboard Widgets. 

In this video, our Solution Expert, Sarah, demonstrates how to use DataGroomr to find and merge duplicate records in Salesforce. 

Create and Analyze In this video, our Solution Expert, Sarah demonstrates how to create a Brushr dataset and analyze this data for quality issues. Email, Phone and Address Verification In this video, our Solution Expert, Sarah demonstrates how to verify phone numbers, email and mailing addresses in...

In this video, our Solution Expert, Sarah, demonstrates how to conveniently deduplicate records as you import them to Salesforce using DataGroomr's IMPORTR module.

In this video, our Solution Expert, Sarah demonstrates how to use SCHEDULR to create automated: Duplication analysis tasks. Deduplication and mass merge tasks. Schedulr can also automate tasks o Mass Convert and Sync to Salesforce. 

Master Record Selection Rules In this video, our Solution Expert, Sarah demonstrates how to use Supervisr to manage master record selection rules. Field Value Rules In this video, our Solution Expert, Sarah demonstrates how to use Supervisr to manage field value rules.

Create, Train and Apply In this video, our Solution Expert, Sarah demonstrates how to use Supervisr to create, train and apply matching models. Clone, Re-train and Default Models In this video, our Solution Expert, Sarah demonstrates how to use Supervisr to clone, re-train models, as well as, des...

In this video, our Solution Expert, Sarah demonstrates how to design Transform Rules and apply them in Brushr and Importr to help standardize/normalize data through bulk updates.  Also, reviews the option to bulk delete bad quality data.