IBM InfoSphere QualityStage vs. MatchX

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

Its suitable for enterprises and business looking for a Data Matching tool.

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

Incentivized

• User-Friendly and Data Management
• No technical expertise, making it accessible for a broader user base.
• Great for Data Mining and Data Matching

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

Incentivized

• The interface could offer even more customization.
• Some users may prefer more frequent feature updates or design refreshes.
• Advanced users might want expanded export or reporting options.

We've never felt the need to migrate to something else.

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

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

Incentivized

• MatchX has enabled a low-maintenance revenue from data mining and token staking.