DGTL Master Data Management vs. Reltio Connected Data Platform

The data model is really flexible, so it should function well across many industries. Reltio Connected Data Platform tends to add new features first to its industrial vertical customers, though, so it may be especially well suited if your use case is specifically supported.

Incentivized

• integration with SFDC, D&B
• Reltio API allows us to build interfaces with ease.
• The beauty of Reltio is Consolidation at any time we can review data at field level from different sources (crosswalk) and configure match merge and survivorship rules to define operational value and approved data can be redistributed to the upstream or downstream systems.
• With Central data governance, enrichment with D&B allows creating trusted data and distribute to various systems.

Incentivized

• UI does not support creating different profile views for an entity based upon customer types as example however we can achieve this by using sub entities ( sub classes). This feature is useful if we are creating profiles in reltio manually.
• Manual export every time we need to pick entities, fields etc does not allow to save templates. workaround is using postman creating predefined API with selected fields, filters and trigger export.
• UI does not support data masking which needed while we maintain PII information
• Potential Matches doesnt auto sort on confidence code so users need to manually select deselect relevant entities which is time consuming and painful process however this issue is when we have more than 4 entities as potential matches.
• It would be beneficial if UI displays data related errors (if any) between Reltio and SFDC.

Incentivized

Good Feedback

Incentivized

Love the UI

Incentivized

We felt Reltio had the best user experience, with flexible graph database technology and a customizable UI. Also important was the ability to look at historical snapshots to see relationships as they existed as of a previous date.

Incentivized

• unifying multiple sources of data = 10+
• Data quality on customer and vendors moved from 65% to 95%
• Reporting quality on operational, finance and sales improved from 70% to 95%

Incentivized