We performed a comparison between Melissa 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."We like having the ability to write our own utilities/software to process our records and store the final output the way we want."
"Our customer database is now significantly more accurate and reliable."
"We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database."
"Allows us to identify cell phones before dialing, and giving us data about callers."
"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."
"Allows us to delete and correct incorrect data to make the searching of our applicant tracking system more consistent and relevant."
"We have only been using this for about two months, but it has sped up our processing significantly. It makes data mining easy and fast. We don't have to spend an entire month gathering correct information on leads. All we need is a list of home addresses, and in minutes we have names and phone numbers to increase our chance of these leads becoming customers."
"Ability to validate addresses, make corrections to address."
"The features that I find to be the most valuable are the extensibility, the integration, and the ease of integration with multiple platforms."
"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."
"The Studio is easy to understand."
"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."
"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."
"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."
"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 file fetch process is impeccable."
"Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines."
"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."
"Did not work as advertized. Needs better results in address parsing, as described on the website."
"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."
"More countries should be supported by Melissa."
"Address validation and parsing in a few countries have room for improvement."
"We would appreciate it if there was a larger database so that we could find information more often. For example, we can search for 10 people and only find the information for three of them, if we are lucky."
"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."
"I would say that some of the support elements need improvement."
"In terms of the solution's technical support, the interactions were satisfactory, but there is room for improvement, especially in managing expectations."
"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."
"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."
"Heap space issues plague us consistently. We maxed it out and it runs fine, then it doesn’t, then it does."
"It would be more helpful if it offered dynamic dashboards that could be directly used by clients for better analysis."
"The ability to change the code when debugging the JavaScript could be improved."
"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."
Earn 20 points
Melissa Data Quality is ranked 9th in Data Quality with 40 reviews while Talend Data Quality is ranked 4th in Data Quality with 20 reviews. Melissa Data Quality is rated 8.4, while Talend Data Quality is rated 8.0. The top reviewer of Melissa Data Quality writes "SSIS MatchUp Component is Amazing". 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". Melissa Data Quality is most compared with Informatica Address Verification, SAP Data Quality Management, Precisely Trillium and Experian Data Quality, whereas Talend Data Quality is most compared with Ataccama DQ Analyzer, Informatica Data Quality, Alteryx, Precisely Trillium and Ataccama ONE Platform. See our Melissa Data Quality vs. Talend Data Quality report.
See our list of best Data Quality vendors and best Data Scrubbing Software vendors.
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