Compare OpenRefine and Oracle Data Quality 
- Users report that Oracle Data Quality excels in its Data Matching capabilities, scoring 8.5, which is particularly beneficial for enterprises needing to ensure data integrity across large datasets. In contrast, OpenRefine shines with a higher score of 9.3, with reviewers mentioning its advanced clustering algorithms that help in identifying duplicates effectively.
- Reviewers mention that OpenRefine's Preventative Cleaning feature is a standout, achieving a score of 9.7, which allows users to proactively clean data before it becomes an issue. Oracle Data Quality, while strong, scores lower at 8.6, indicating that users may find it less effective in this area.
- G2 users highlight the Correction functionality in OpenRefine, which received a score of 9.5, as a key feature that simplifies the process of fixing data errors. In comparison, Oracle Data Quality's score of 8.6 suggests that while it offers correction features, they may not be as user-friendly or efficient as those in OpenRefine.
- Users on G2 report that Oracle Data Quality's Quality Audits feature, scoring 8.7, provides robust insights into data quality over time, which is crucial for enterprise-level data governance. OpenRefine, however, does not have a comparable feature, which may limit its appeal for users focused on long-term data quality management.
- Reviewers mention that the Ease of Use for OpenRefine is a significant advantage, with a score of 9.1, making it accessible for small businesses and users without extensive technical expertise. Oracle Data Quality, with a score of 7.9, may present a steeper learning curve, particularly for new users.
- Users say that the Quality of Support for Oracle Data Quality, rated at 8.4, is generally reliable, with many users appreciating the responsiveness of the support team. In contrast, OpenRefine's support, rated at 7.7, has received mixed reviews, with some users expressing a desire for more comprehensive documentation and assistance.
OpenRefine runs in the browser, supports a wide variety of data formats and is loaded with features to make data cleaning, preparation and structuring a breeze. I especially like the built-in algorithms to identify duplicates of data. In general, OpenRefine...
I had a really hard time building my own code into the different column sections.
Our Email Marketing Campaigns were not getting enough open,click rate and many were bounced too. Keeping my emails away from inbox. I finally found Email Validation which removes all dead and bounced emails which do no exist anymore. Sending email campaign...
Auto queries on data entry - which is entered as query stated or per guidelines. The system has set practices but will not allow you to enter per their requests
OpenRefine runs in the browser, supports a wide variety of data formats and is loaded with features to make data cleaning, preparation and structuring a breeze. I especially like the built-in algorithms to identify duplicates of data. In general, OpenRefine...
Our Email Marketing Campaigns were not getting enough open,click rate and many were bounced too. Keeping my emails away from inbox. I finally found Email Validation which removes all dead and bounced emails which do no exist anymore. Sending email campaign...
I had a really hard time building my own code into the different column sections.
Auto queries on data entry - which is entered as query stated or per guidelines. The system has set practices but will not allow you to enter per their requests
