We performed a comparison between Alteryx and Talend Data Quality based on real PeerSpot user reviews.
Find out what your peers are saying about Alteryx, RapidMiner, SAP and others in Predictive Analytics."The most valuable feature of Alteryx is its performance. It is a powerful solution."
"The scheduling within the solution is excellent."
"Predictive models, which are easy to use, and help a lot with fast design and deployment."
"The filtering is fast, and it provides a search tool that is great."
"I believe that the ability to leverage the gallery for scalability, as well as the general data blending functionality, is most beneficial to our core-based users."
"It has everything that one needs. Whatever you want to do with the data can be done with Alteryx."
"I like that I can merge data from different sources into one place."
"Its initial setup is easy."
"It lowers the amount of time in development from weeks to a day."
"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."
"With its frequency function, we were able to pick a line of business to be addressed first in one of our conversion projects."
"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."
"We are able to get emails from URLs very easily using this function when others fail."
"The file fetch process is impeccable."
"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 solution just lacks in terms of data visualization. That is why we use Tableau and Qlik in our organization. They help to pick up the slack. If data visualization was added, Alteryx would be a very good tool, and much more complete."
"It should have Linux support. It currently supports only Windows. It does not support any other platform. Its price should also be lower. Their US partner management program is actually unresponsive. One of the reasons why we don't have a formalized partnership plan with them is because their partner management team is atrociously unresponsive. This is something that they need to change."
"They should work on its pricing."
"All of the reports are migrated or exported in an Excel file, and most of the time, a business intelligence tool is required. They could have better reporting. The aesthetic could be improved."
"The event handling, such that the file system watcher, is in need of improvement."
"The learning curve is long, and there is lack of e-learning; the tool is not user-friendly to a non-technical user."
"The screen when you are looking into your workflows and your ETL processes needs to be improved. You cannot manage it very well."
"It would be great to create the final users' visualization within Alteryx."
"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."
"If the SQL input controls could dynamically determine the schema-based on the SQL alone, it would simplify the steps of having to use a manually created and saved schema for use in the TMap for the Postgres and Redshift components. This would make things even easier."
"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."
"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."
"The performance is one area that Talend Data Quality could improve in because large volumes take a lot of time."
"It would be more helpful if it offered dynamic dashboards that could be directly used by clients for better analysis."
"There are too many functions which could be streamlined."
"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."
Alteryx is ranked 1st in Predictive Analytics with 74 reviews while Talend Data Quality is ranked 4th in Data Quality with 20 reviews. Alteryx is rated 8.4, while Talend Data Quality is rated 8.0. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". 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". Alteryx is most compared with KNIME, Databricks, Dataiku Data Science Studio, RapidMiner and Qlik Sense, whereas Talend Data Quality is most compared with Ataccama DQ Analyzer, Informatica Data Quality, Precisely Trillium, Informatica Address Verification and Informatica Cloud Data Quality.
We monitor all Predictive Analytics 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.
