IBM InfoSphere QualityStage vs. Vertify

Standardization of data using rules for names and addresses. Possibility of building our own rules to standardize other data. Contruction of complex rules of matching and consolidation of data. Native integration with ETL tools and data governance.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

I would recommend it, as VertifyData exactly fit our use case. I can't speak for all use cases and all connectors - naturally - but the ones we are using and have explored so far, work perfectly well. Also, being a person myself that is not fluent in SQL or JSON or API language in general, I was still able to create all workflows our company needed myself. Which I consider a huge benefit.

• Create rules
• Standardization and normalization of data
• Integration with DataStage

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Communication.
• Follow up.
• They're constantly trying to improve.

• Should include all the data profiling functionality
• Better features to tune matching capability
• Include AI to automatically recommend actions to improve processes

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Automated error trouble-shooting is not always clear/helpful
• Clearly distinguishing internal errors vs. external errors
• Perhaps a blog where users can interact with questions + solutions

Creating a mapping between source and target while also using lookups and transformations is not trivial. And VertifyData solved this reasonably well, at least all users in my organization understood it pretty quickly.

It is not the easiest user interface to read/understand. However, once you understand how it works, then using it is not that bad. It's hard to remember what feature is listed under what tab (Manage vs. Define). A suggestion would be to get all call to actions on the same page

It is a robust tool. It can be integrated with several DB. It works very well with DS. You can create your rules, and define the percentage of standardization or normalization

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Vertify offered more flexibility and was presented as a simple solution. In reality, it is more complex that we envisioned and we have never fully utilized our tools due to the lack of ability to configure things properly.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Improving Data Quality
• Reducing costs due to better Data Quality
• Single view of customer / product
• Better data governance

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Independently, teams are able to carry out their process with less communication and at a higher level of accuracy.
• VertifyData is actively taking into consideration, consulting, and supporting our plans to build out the business