Compare Oracle Data Quality vs. StarDQ

Oracle Data Quality is ranked 3rd in Data Quality with 1 review while StarDQ which is ranked 34th in Data Quality. Oracle Data Quality is rated 10.0, while StarDQ is rated 10.0. The top reviewer of Oracle Data Quality writes "A little complex in terms of the designing the infrastructure but not too complex". On the other hand, Oracle Data Quality is most compared with Informatica Data Quality, IBM QualityStage and Trillium TS Quality , whereas StarDQ is most compared with DataFuse.
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Oracle Data Quality Logo
2,667 views|512 comparisons
StarDQ Logo
30 views|25 comparisons
Most Helpful Review
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Ranking
3rd
out of 37 in Data Quality
Views
2,667
Comparisons
512
Reviews
1
Average Words per Review
377
Avg. Rating
10.0
34th
out of 37 in Data Quality
Views
30
Comparisons
25
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 100% of the time.
Also Known As
Datanomic
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Oracle
StarCom
Overview
Oracle Enterprise Data Quality delivers a complete, best-of-breed approach to party and product data, resulting in trustworthy master data that integrates with applications to improve business insight.

A powerful, real time enterprise solution for Cleansing, De-duping, and enriching the data. By integrating StarDQ Solution, organizations can cleanse, match and unify data across multiple data sources and data domains, to create a strategic, trustworthy, valuable asset that enhances decision making power, reduce expenses and ensure seamless customer interaction.

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Learn more about StarDQ
Sample Customers
Roka Bioscience, Statistics Centre _ Abu Dhabi , Raymond James Financial inc., CaixaBank, Industrial Bank of Korea, Posco, NHS Business Services Authority, RWE Power, LIFE Financial Group, North East Worcestershire, Pfizer, Roehampton University, Tata Docomo, Tunstall
We monitor all Data Quality reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
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