SQL Power Data Quality vs Talend Data Quality comparison

"The Nomo, select form, and so on are the most valuable features."

"It is a scalable solution. We have over 1,000 SQL Power Data Quality users in our organization."

"The solution is able to integrate with many systems and other products."

"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 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."

"The features that I find to be the most valuable are the extensibility, the integration, and the ease of integration with multiple platforms."

"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."

"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."

"The most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work."

"The only area of improvement that we've come across within the solution was the portfolio roadmap creation. There's a bit of limitation there, but otherwise, the tool itself is very good."

"The normalization factor should be improved so that it is better scaled. It should be more user-friendly."

"Downtime issues should be improved."

"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."

"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."

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

"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."

"I would say that some of the support elements need improvement."

"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."

"The performance is one area that Talend Data Quality could improve in because large volumes take a lot of time."

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

"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."

"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."

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

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