We performed a comparison between Syniti 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."The major benefits of Syniti Data Quality stem from the productivity and flexibility it offers to users."
"The customer service and support is good."
"With Syniti Data Quality, you can integrate SAP and directly fix errors from Syniti Data Quality instead of logging into SAP and then fixing them."
"Syniti has built-in 80% of the solution, and we only need to customize 20 to 25% of the features. It is easy to run and pre-load reports."
"tLogRows are also great for finding bad data."
"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 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."
"It offers advanced features that allow you to create custom patterns and use regular expressions to identify data issues."
"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."
"The Studio is easy to understand."
"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."
"The solution is customizable."
"It would be good if Syniti Data Quality could integrate more AI in the future."
"In Syniti Data Quality, data extraction is an area with certain shortcomings where improvements are required."
"The customization of the data needs improvement. We need to build basic SQL queries rather than being able to do it within the tool. We need to be able to analyze the SQL queries and then rerun them based on customer usage."
"The loading mechanisms and administration processes, particularly in setting up connections and deploying the system, need improvement."
"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."
"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."
"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."
"I would say that some of the support elements need improvement."
"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."
"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."
"When we upgraded to Version 6.4.1, we tried using a GIT repository instead of a SVN repository. After a few incidents where things disappeared and changes were not saved, we decided to go back to a SVN repository."
Syniti Data Quality is ranked 7th in Data Quality with 4 reviews while Talend Data Quality is ranked 4th in Data Quality with 20 reviews. Syniti Data Quality is rated 8.6, while Talend Data Quality is rated 8.0. The top reviewer of Syniti Data Quality writes "A highly stable solution that can be deployed very quickly and easily". 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". Syniti Data Quality is most compared with SAP Data Services, SAP Data Quality Management and Informatica Cloud Data Quality, whereas Talend Data Quality is most compared with Ataccama DQ Analyzer, Informatica Data Quality, Alteryx, Precisely Trillium and Informatica Address Verification. See our Syniti Data Quality vs. Talend Data Quality report.
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