Ataccama DQ Analyzer vs Talend Data Quality comparison

"The data profile itself is excellent. You can understand the quality of the data in layman's terms."

"It is also easy to deploy."

"​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."

"tLogRows are also great for finding bad data."

"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."

"The Studio is easy to understand."

"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."

"We are able to get emails from URLs very easily using this function when others fail."

"The file fetch process is impeccable."

"Although DQA can fetch data from most of the commonly used data sources, it has limited modifiers to get data, meaning that the number of technologies from which the data can be acquired is limited. For example, DQA does not support fetching data from Twitter or Facebook. Many competitors have this feature."

"They could focus more on marketing the product. The current marketing strategy is not working."

"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."

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

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

"The ability to change the code when debugging the JavaScript could be improved."

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

"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."

"It would be more helpful if it offered dynamic dashboards that could be directly used by clients for better 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."

"There is no need to buy a license. You can just download it and use it for free."

"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'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."

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

"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."