Informatica Cloud Data Quality vs. Oracle Enterprise Data Quality

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Informatica Cloud Data Quality
Score 6.0 out of 10
N/A
The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.N/A
Oracle Data Quality
Score 9.5 out of 10
N/A
Oracle Enterprise Data Quality is, as the name would suggest, a data quality offering from Oracle for enterprises.N/A
Pricing
Informatica Cloud Data QualityOracle Enterprise Data Quality
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Informatica Cloud Data QualityOracle Data Quality
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Informatica Cloud Data QualityOracle Enterprise Data Quality
Features
Informatica Cloud Data QualityOracle Enterprise Data Quality
Data Quality
Comparison of Data Quality features of Product A and Product B
Informatica Cloud Data Quality
8.9
Ratings
2% above category average
Oracle Enterprise Data Quality
9.6
Ratings
10% above category average
Data source connectivity9.30 Ratings9.50 Ratings
Data profiling9.20 Ratings10.00 Ratings
Master data management (MDM) integration8.90 Ratings9.50 Ratings
Data element standardization8.20 Ratings9.50 Ratings
Match and merge8.70 Ratings9.50 Ratings
Address verification9.00 Ratings9.50 Ratings
User Ratings
Informatica Cloud Data QualityOracle Enterprise Data Quality
Likelihood to Recommend
9.2
(0 ratings)
9.5
(0 ratings)
Likelihood to Renew
6.6
(0 ratings)
-
(0 ratings)
Usability
8.0
(0 ratings)
-
(0 ratings)
Availability
9.0
(0 ratings)
-
(0 ratings)
Performance
9.0
(0 ratings)
-
(0 ratings)
Online Training
10.0
(0 ratings)
-
(0 ratings)
Implementation Rating
10.0
(0 ratings)
-
(0 ratings)
Product Scalability
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Informatica Cloud Data QualityOracle Enterprise Data Quality
Likelihood to Recommend
We used Informatica Data Quality to measure the "Data Quality Score" of internal and external reports at my company. Business users set up data profiling and prepared detailed analysis documents for business analysts. and developers developed Data Quality Mapplets for other IT teams to import their Informatica Power Center repositories. Results are stored in a centralized data quality space and then reported and summarized to related business users in detailed ways. At the end of each project, we are now able to place a "Data Quality Score" watermark score on each report involved.
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  • Ease of adding localized and customized data quality formulations (for instance asking for Turkish Citizenship Number from governmental web service and checking whether data is the same with the output).
  • Finding the "golden record" from the duplicated records.
  • Adding and/or merging missing information from different data sources.
  • Using patterns and statistical functions to complete the data.
  • Address verification (can be localized).
  • Parsing of combination of records.
  • Enriching required data from free text (story told) inputs.
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Pros
  • Watch the data real time- After creating the job the data quality engine checks and run the custom rules creating a navigation window at the bottom for review and accessing the data right away.
  • Character Set Mapping
  • Makes sense of our own data, which in turn gives us confidence that we can provide to the end users. IDQ helped us with erroneous data in accounting and HR for accurate and immaculate reports
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  • Address verification helps you filter bad data out and improve your data quality.
  • Strength by DnB enriched information to address the correct customer by address.
  • expert data profiling to help us quickly understand our current data health.
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Cons
  • Several partnerships diminishing the value of technologies
  • Unable to get list of objects from Repository (like sources & targets) that don't have any dependency
  • Scheduling: The built-in scheduling tool has many constraints such as handling Unix/VB scripts etc. Most enterprises use third party tools for this.
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  • Updates are few and far between as this has transitioned to the Cloud and is the core engine for DIPC (Data Integration Platform Cloud).
  • Needs governance around the tool if multiple people are running reports (e.g. if someone is running a process, it locks out other users).
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Likelihood to Renew
I gave a rating of 8 due to the fact that we use Informatica for both our data quality product and ETL product. Having both integrated makes it so much easier. Microsoft had a similar product of finding duplicates, but at the time it didn't seem mature enough. The usability also in IDQ was pretty easy to navigate and use.
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Usability
Easy to use not only for developers but also business users
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Reliability and Availability
The application works well except an occasional error out while using the system. It usually gets fixed when restarting the Infa server
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Performance
Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.
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Alternatives Considered
Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of working closely with several programs. Finally, Informatica Data Quality design is authentic and allows personalization.
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Oracle Enterprise Data Quality is affordable and I find it more resourceful. Using it is easy too thanks to the improved UI.
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Scalability
Scalability works as expected and it is truly an enterprise system.
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Return on Investment
  • Integration with tools like PowerCenter helped faster delivery of product, and at the same time conversion
  • Reduce overall project cost due to bad data , bad quality, exceptions identified nearing go-live and post production
  • Employee efficiency is increased exponentially due to more automated, customized tool
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  • Details verification, for instance, address ensure the quality of every operation is sustained.
  • Further, sales analytics improves the market share as customers get to apprehend the business needs.
  • Oracle Data Quality has consistent data connectivity, a standard way of improvising business requirements.
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ScreenShots