We performed a comparison between Melissa Data Quality and Talend Data Quality based on real PeerSpot user reviews.
Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality."Through more accurate data, our marketing department has been able to increase delivery and conversion rates through email direct marketing initiatives."
"The high value in this tool is its relatively low cost, ease of use, tight integration with SSIS, superior performance (compared to competitors), and attribute-level advanced survivor-ship logic."
"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."
"It saves a huge amount of time. Before using this service, we used a vendor that manually ran our lists through this NCOA list, which might have taken one to three business days to return the file. This was a huge bottleneck in our process, and the data returned was not always accurate. After switching to Melissa Data’s SmartMover, the process has been reduced to between ten minutes and three hours, depending on the amount of records sent."
"We like having the ability to write our own utilities/software to process our records and store the final output the way we want."
"Be confident that the scalability and load are not going to be an issue with the services. "
"Helps our organization provide accurate address information to our customers for direct mailing (household) and other campaigns they want to do."
"The customers' addresses are now complete, correct and follow one consistent format."
"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."
"The most valuable feature lies in the capability to assign data quality issues to different stakeholders, facilitating the tracking and resolution of defective work."
"It’s easy to monitor the processes. Every morning I’ll open the Talend Administration Center to check the status of the process. Within seconds I’m able to see which process ran successfully and which have failed and why they failed."
"It reduces the QA effort immensely by handling most of the test scenarios in a reusable way."
"The file fetch process is impeccable."
"The numerous components provided by Talend mean you’re able to create jobs quickly and efficiently."
"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."
"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."
"An area for improvement is where an end customer's address is not found in the Melissa Data database, even though it is a valid address."
"Did not work as advertized. Needs better results in address parsing, as described on the website."
"It really hasn't given us a phone number for the owner of the property, and that's one thing I'd really like to be getting. Either a phone number or email."
"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."
"Tech support at Melissa Data was very quick to wash their hands of an issue and say it's IT policies on my side that are causing the issue. There was no offer to try and find a work-around. Just an overwhelming attitude of "it’s not our problem.""
"Many issues, sometimes I have to completely log out and start over."
"I wish there was a way to do a "test run" and see what a particular format will give you."
"It would be helpful if a list of the codes and explanations could be included."
"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."
"It would be more helpful if it offered dynamic dashboards that could be directly used by clients for better analysis."
"The performance is one area that Talend Data Quality could improve in because large volumes take a lot of time."
"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."
"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."
"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."
"SQL for displaying underlying data in non-match results does not work."
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 Informatica Address Verification.
See our list of best Data Quality vendors and best Data Scrubbing Software vendors.
We monitor all Data Quality 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.
