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IBM Infosphere Information Analyzer vs Informatica Cloud Data Quality comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 6, 2025

Review summaries and opinions

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

Categories and Ranking

IBM Infosphere Information ...
Ranking in Data Quality
7th
Average Rating
7.6
Reviews Sentiment
5.8
Number of Reviews
6
Ranking in other categories
No ranking in other categories
Informatica Cloud Data Quality
Ranking in Data Quality
3rd
Average Rating
8.0
Reviews Sentiment
5.9
Number of Reviews
17
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Data Quality category, the mindshare of IBM Infosphere Information Analyzer is 2.5%, up from 2.2% compared to the previous year. The mindshare of Informatica Cloud Data Quality is 4.4%, down from 8.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Market Share Distribution
ProductMarket Share (%)
Informatica Cloud Data Quality4.4%
IBM Infosphere Information Analyzer2.5%
Other93.1%
Data Quality
 

Featured Reviews

Tirthankar Roy Chowdhury - PeerSpot reviewer
Accessible from anywhere and easy to learn even for non-technical users, but needs more connectors and faster issue resolution from technical support
What could be improved or added to IBM Infosphere Information Analyzer is more connectors. This solution comes in a package with IBM InfoSphere DataStage and is missing a lot of connectors to various, new data sources, so IBM needs to work on that area. Compared with competitors such as Informatica and Alation which acquired other small companies to work on the connectors, IBM has not done any testing and has tried to develop the connectors in-house, but that's taking a lot of time. As a result, my company is unable to connect to a lot of data sources, particularly modern data sources.
Mehmet SukruKaya - PeerSpot reviewer
Improved data quality significantly enhances project efficiency and effectiveness
I am not utilizing the data quality rules management part yet. We had a bad experience before Informatica Cloud Data Quality. We started a data analytics project that took more than three months of wasted time because we couldn't use the data to create the optimization model. If we have an application like Informatica Cloud Data Quality or a data quality platform, we can finish the project in less than three months. This is the on-prem data that we ingested. We don't use any cloud data that we have. For now, we are just using the on-prem data, and we don't have any integration from the data outside of the on-prem. I would recommend it to other users. On a scale of 1-10, I rate this solution a 9.

Quotes from Members

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

Pros

"You can also schedule and run data quality on the critical data elements on the databases."
"What's most useful in IBM Infosphere Information Analyzer is you can access it from anywhere. It's also pretty easy to learn, so even non-technical business people use it and found the solution easy to learn."
"The user-friendliness and performance of Informatica is quite impressive."
"I was responsible for installing Informatica Cloud Data Quality on Google infrastructure, which was straightforward."
"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 profiling features are much better than the on-premise version."
"Initial setup was fairly easy."
"The quality of the data improves with Informatica Cloud Data Quality."
"Stability-wise, I rate the solution a ten out of ten."
"The most beneficial feature of Informatica Cloud Data Quality is it's cloud-based."
 

Cons

"What could be improved or added to IBM Infosphere Information Analyzer is more connectors. This solution comes in a package with IBM InfoSphere DataStage and is missing a lot of connectors to various, new data sources, so IBM needs to work on that area. Compared with competitors such as Informatica and Alation which acquired other small companies to work on the connectors, IBM has not done any testing and has tried to develop the connectors in-house, but that's taking a lot of time. As a result, my company is unable to connect to a lot of data sources, particularly modern data sources."
"The solution is outdated and is not on cloud."
"I used to use this tool more but recently we have been using another tool that we feel is better because it handles spatial data. Informatica Cloud Data Quality could improve by adding the ability to handle spatial data."
"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."
"Support response time could be better."
"I definitely will not recommend Informatica Cloud Data Quality because it's very hard to manage the licensing model and the price is very high."
"In certain domains, I am looking for material-level match features that are not customizable. The current solution requires code-writing and tweaking, while other solutions offer material-level matches."
"I remember when I used it, there was some limitation in one of the data quality dimensions. I was not able to perform certain tasks on the cloud version, even though I could do them on the data center version."
"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."
"If given the opportunity, I would like to address these concerns, particularly with regard to enhancing the end-user experience."
 

Pricing and Cost Advice

"For the licensing cost of IBM Infosphere Information Analyzer, I have no information on the exact cost, but as it's bundled with other IBM products such as IBM InfoSphere Information Governance Catalog and IBM InfoSphere DataStage, the bundle is expensive when compared to competitor pricing."
"Informatica Cloud Data Quality is a costly solution."
"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."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
11%
Manufacturing Company
11%
Computer Software Company
11%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise9
 

Questions from the Community

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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?
I think it would be very useful to have the same features on the data center version available on the cloud version. I remember when I used it, there was some limitation in one of the data quality ...
What is your primary use case for Informatica Cloud Data Quality?
I worked on a project where we had to use these tools to execute the data quality requirements from assessment perspectives to scorecards and similar tasks. I haven't used any other tools, so I can...
 

Also Known As

Information Analyzer
Cloud Data Quality Radar
 

Overview

 

Sample Customers

Integra LifeSciences, Longjiang Bank Corp., Webster University, Swedish Armed Forces, Edith Cowan University, Premier, PRISA Digital, TIAA CREF
Freddie Mac, Rabobank
Find out what your peers are saying about IBM Infosphere Information Analyzer vs. Informatica Cloud Data Quality and other solutions. Updated: September 2025.
868,759 professionals have used our research since 2012.