Syniti Data Quality vs Talend Data Quality comparison

"The customer service and support is good."

"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."

"The major benefits of Syniti Data Quality stem from the productivity and flexibility it offers to users."

"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."

"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."

"With its frequency function, we were able to pick a line of business to be addressed first in one of our conversion projects."

"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."

"I like idea of storing the results of Data Quality jobs in a DB and having the ability to run reports in the DB to show a dashboard of quality metrics."

"​It lowers the amount of time in development from weeks to a day.​"

"The Studio is easy to understand."

"It has definitely streamlined certain processes.​"

"tLogRows are also great for finding bad data."

"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."

"In Syniti Data Quality, data extraction is an area with certain shortcomings where improvements are required."

"It would be good if Syniti Data Quality could integrate more AI in the future."

"The loading mechanisms and administration processes, particularly in setting up connections and deploying the system, need improvement."

"You can't join more than two tables for analysis."

"If we encounter issues, it’s most likely when using the Talend Open Studio. The studio can be slow, get stuck, or crash. But again, it can be caused by the resources of your machine or your connection with the repository. If we encounter issues with the Studio we restart the Studio. In emergencies, we create and use a new workspace."

"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."

"There are too many functions which could be streamlined."

"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."

"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."

"In redundancy analysis, the query is failing to bring non-matched records. This query is an internal script. There is no way (that I know of) to fix this syntax error for future runs."

"I would rate the pricing a six out of ten, where one is cheap, and ten is expensive."

"The solution is expensive."

"It's a subscription-based platform, we renew it every year."

"It is cheaper than Informatica. Talend Data Quality costs somewhere between $10,000 to $12,000 per year for a seat license. It would cost around $20,000 per year for a concurrent license. It is the same for the whole big data solution, which comes with Talend DI, Talend DQ, and TDM."

"I would advise to first take a look and at the Open Studio edition. Figure out what you need and purchase the appropriate license."

"We did not purchase a separate license for DQ. It is part of our data platform suite, and I believe it is well-priced."

"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."