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Informatica Cloud Data Quality vs Oracle Data Quality comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Informatica Cloud Data Quality
Ranking in Data Quality
3rd
Average Rating
8.4
Number of Reviews
11
Ranking in other categories
No ranking in other categories
Oracle Data Quality
Ranking in Data Quality
15th
Average Rating
8.4
Number of Reviews
8
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of December 2024, in the Data Quality category, the mindshare of Informatica Cloud Data Quality is 3.0%, up from 2.0% compared to the previous year. The mindshare of Oracle Data Quality is 1.7%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality
 

Featured Reviews

TaherDungrawala - PeerSpot reviewer
Has good reusability and CDI features
I use Collibra Data Quality. I switched to Informatica because Collibra cannot integrate. Colibra Cloud Data Quality is a very basic tool. There is no integration capability. If you have problem records, there is no fix to remediate them using the same tool. With Informatica, you can integrate with CDI and then create a remediation plan.
Venkatraman Bhat - PeerSpot reviewer
Fast, has good extraction, validation, and transformation features, and provides good support
Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"We primarily used Cloud Data Profiling to connect with Cloud Data Governance, a tool also used by Teva. This integration allowed users to access data quality results within the data governance catalog."
"The most valuable feature is the rule specification."
"The reusability factors are nice. The Cloud Data Quality is much better. A major flaw in the previous version was integration with the catalog, which is now seamless."
"Stability-wise, I rate the solution a ten out of ten."
"The profiling features are much better than the on-premise version."
"One of the most valuable features of Informatica Cloud Data Quality is Master Data Management. You can write code to build your logic rules to check the quality."
"The user-friendliness and performance of Informatica is quite impressive."
"An advantage is its seamless integration with other Informatica capabilities, making data quality a deeply embedded part of the solution."
"I have found the most valuable features to be data cleansing and deduplication."
"With Oracle Data Quality, the most valuable feature is entity matching."
"The features I like most about Oracle Data Quality include extraction, transformation, and validation, which makes it a multipurpose product such as Oracle GoldenGate and Oracle Data Integrator. I also like that Oracle Data Quality is very fast, so you can use it for a large volume of data within a short period. You have to do the validation very quickly, so the solution helps in that area of data quality. Another feature of Oracle Data Quality that I like is the MDM (Master Data Management) where you'll have a single source of protection, and this makes the solution perfect and helpful to my company."
"Once it is set up, it is easy to use and maintain."
 

Cons

"If given the opportunity, I would like to address these concerns, particularly with regard to enhancing the end-user experience."
"Accessing data as a service is essential, especially for validations requiring external data services. This goes beyond basic syntactic checks, like ensuring an email address contains the @ symbol or .com domain. Instead, it's about advanced validation, such as verifying if an email address exists or if a phone number is valid."
"In the on-premises version, features like web service consumer and web service provider are available, but these functionalities are currently unavailable in the cloud edition."
"The integration with older technology and cloud quality needs improvement."
"Informatica Cloud Data Quality could improve by adding more algorithms for matching and mastering. We currently only have five or six. Additionally, the parallelism in data is better in other solutions, such as IBM."
"Support response time could be better."
"Logical views are a little bit behind in comparison to the on-premise version."
"The high price of the product is an area of concern where improvements are required."
"Though validation is good and fast enough in Oracle Data Quality, an area for improvement is the accuracy of the validation. Though the solution offers multidimensional validation, it needs a bit more improvement in the accuracy aspect because smaller products can offer better accuracy in terms of validation compared to Oracle Data Quality. What I'd like to see from the solution in its next release, is an increase in compliances and regulations that would allow it to cover all industries because multiple verticals demand data quality nowadays, and this improvement will be helpful as Oracle Data Quality is an in-built delivered solution."
"If the length of time required for deployment was reduced then it would be very helpful."
"Oracle Data Quality should integrate with data warehousing solutions such as Azure and CWS Office. For example, having the ability to integrate with tools, such as Azure Synapse and SQL data warehousing would be a great benefit."
"Oracle is currently not that intuitive. We need to use programmers to write code for a lot of the procedures. We need to have them write CL SQL code and write a CL script."
 

Pricing and Cost Advice

"The licensing costs attached to the solution are pretty high, but then, with the cloud model, the prices depend on what it provides for the value of money, which I feel was very high."
"We pay for a yearly subscription."
"Informatica Cloud Data Quality is a costly solution."
"The vendor needs to revisit their pricing strategy."
"The price of this solution is comparable to other similar solutions."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
10%
Computer Software Company
8%
Logistics Company
7%
Financial Services Firm
32%
Manufacturing Company
8%
Computer Software Company
8%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Informatica Cloud Data Quality?
The profiling features are much better than the on-premise version.
What needs improvement with Informatica Cloud Data Quality?
Accessing data as a service is essential, especially for validations requiring external data services. This goes beyond basic syntactic checks, like ensuring an email address contains the @ symbol ...
What is your primary use case for Informatica Cloud Data Quality?
We use the solution to validate emails, telephone numbers, and postal codes. It can also create some data quality rules using the Cloud app's data quality function.
Ask a question
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Also Known As

Cloud Data Quality Radar
Datanomic
 

Overview

 

Sample Customers

Freddie Mac, Rabobank
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,
Find out what your peers are saying about Informatica Cloud Data Quality vs. Oracle Data Quality and other solutions. Updated: December 2024.
824,067 professionals have used our research since 2012.