We performed a comparison between Informatica Data Quality and Talend Data Quality based on real PeerSpot user reviews.
Find out in this report how the two Data Quality solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I am impressed by the solution's interface."
"The user interface is flexible and the visibility of the data flow is amazing."
"I give the stability a ten out of ten."
"I do find Informatica Data Quality is stable. It generally maintains a high level of reliability and stability, making it an asset."
"It is very useful for testing purposes and designing mappings for small projects. If you go for IDQ in the mapping itself, you can see the data. You can then correct it, and test it so easily. It is working fine. It is also stable, scalable, and easy to deploy."
"The profiling feature in Informatica Data Quality is incredibly effective for data governance."
"Seeing the data in the mapping itself is really nice."
"We are able to set rules, establish a data quality management platform, and monitor the quality."
"It’s easy to monitor the processes. Every morning I’ll open the Talend Administration Center to check the status of the process. Within seconds I’m able to see which process ran successfully and which have failed and why they failed."
"The Studio is easy to understand."
"The jobs are visual and this has improved collaboration between colleagues. It’s much easier to understand a visual job than a piece of Java code."
"I really like the fact that there are no out-of-the-box solutions regarding the development of jobs. Other vendors may have modules which cleanse your addresses. In Talend, you have the freedom to completely develop the process yourself. This can be tricky, but it also makes it fun."
"It lowers the amount of time in development from weeks to a day."
"tLogRows are also great for finding bad data."
"This product speeds up the unit testing and QA for specific test scenarios. As a result, the development output quality can be evaluated and adjusted."
"It is saving a lot of time. Today, we can mask around a hundred million records in 10 minutes. Masking is one of the key pieces that is used heavily by the business and IT folks. Normally in the software development life cycle, before you project anything into the production environment, you have to test it in the test environment to make sure that when the data goes into production, it works, but these are all production files. For example, we acquired a new company or a new state for which we're going to do the entire back office, which is related to claims processing, payments, and member enrollment every year. If you get the production data and process it again, it becomes a compliance issue. Therefore, for any migrations that are happening, we have developed a new capability called pattern masking. This feature looks at those files, masks that information, and processes it through the system. With this, there is no PHI and PII element, and there is data integrity across different systems. It has seamless integration with different databases. It has components using which you can easily integrate with different databases on the cloud or on-premise. It is a drag and drop kind of tool. Instead of writing a lot of Java code or SQL queries, you can just drag and drop things. It is all very pictorial. It easily tells you where the job is failing. So, you can just go quickly and figure out why it is happening and then fix it."
"Informatica is very expensive."
"Considering internal data from legacy systems, it is quite difficult to know if Informatica Data Quality meets that high level of accuracy criteria."
"Exploring the possibility of incorporating AI capabilities that can suggest additional rules would significantly streamline our data analysis process following data profiling."
"The tools required to migrate existing mappings and server rules through cloud data quality are not available."
"I would like to see better visuals for business users, such as a dashboard where they can precisely track where problems are."
"It can be improved in terms of performance and execution. I'm expecting better performance. It currently has some restrictions in terms of execution. For example, if we want to run it in the command mode and execute it, there are some restrictions, and we are facing some issues with a huge volume of data. These restrictions are not there in Informatica PowerCenter because we are able to execute a huge volume of data, and there are more ways to execute it."
"There is room for improvement in the Data Marketplace aspect."
"One area that could use improvement is the speed of the web interfaces. At present, they are very slow. I think it is essential that we are original and robust on-premises."
"I would say that some of the support elements need improvement."
"The performance is one area that Talend Data Quality could improve in because large volumes take a lot of time."
"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."
"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."
"There are too many functions which could be streamlined."
"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."
"Finding assistance with issues can be spotty. With Python, there are literally millions of open source answers which are recent and apply to the version that we are using."
"If the SQL input controls could dynamically determine the schema-based on the SQL alone, it would simplify the steps of having to use a manually created and saved schema for use in the TMap for the Postgres and Redshift components. This would make things even easier."
Informatica Data Quality is ranked 1st in Data Quality with 18 reviews while Talend Data Quality is ranked 4th in Data Quality with 20 reviews. Informatica Data Quality is rated 7.8, while Talend Data Quality is rated 8.0. The top reviewer of Informatica Data Quality writes "Offers cloud version, good connectivity and data profiling features ". On the other hand, the top reviewer of Talend Data Quality writes "Saves a lot of time, good ROI, seamless integration with different databases, and stable". Informatica Data Quality is most compared with Informatica Cloud Data Quality, Trillium Quality, Oracle Data Quality, IBM Infosphere Information Analyzer and Microsoft Data Quality Services, whereas Talend Data Quality is most compared with Ataccama DQ Analyzer, Alteryx, Precisely Trillium and Ataccama ONE Platform. See our Informatica Data Quality vs. Talend Data Quality report.
See our list of best Data Quality vendors.
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.
