We performed a comparison between Oracle Data Quality and Talend Data Quality based on real PeerSpot user reviews.
Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality."With Oracle Data Quality, the most valuable feature is entity matching."
"Once it is set up, it is easy to use and maintain."
"I have found the most valuable features to be data cleansing and deduplication."
"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."
"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."
"Provides a flexible development environment to the coder."
"It offers advanced features that allow you to create custom patterns and use regular expressions to identify data issues."
"The solution enables robust data matching, merging, survivorship, and Data Stewardship that can be a part of data quality workflows or true master data management."
"We have used value frequency and patterns. We have been it impressed with these functions as they have helped us in making decisions in transformation work."
"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."
"It has definitely streamlined certain processes."
"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."
"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."
"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."
"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."
"If the length of time required for deployment was reduced then it would be very helpful."
"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."
"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."
"You can't join more than two tables for analysis."
"There are too many functions which could be streamlined."
"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."
"NullPointerExceptions are going to be the death of me and are a big reason for our transition away from Talend. One day, it is fine with a 1000 blank rows, then the next day, it will find one blank cell and it breaks down."
"The performance is one area that Talend Data Quality could improve in because large volumes take a lot of time."
Oracle Data Quality is ranked 10th in Data Quality with 8 reviews while Talend Data Quality is ranked 4th in Data Quality with 20 reviews. Oracle Data Quality is rated 8.4, while Talend Data Quality is rated 8.0. The top reviewer of Oracle Data Quality writes "Fast, has good extraction, validation, and transformation features, and provides good support". 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". Oracle Data Quality is most compared with Informatica Data Quality, whereas Talend Data Quality is most compared with Ataccama DQ Analyzer, Informatica Data Quality, Alteryx, Precisely Trillium and Informatica Cloud Data Quality.
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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.