We performed a comparison between Melissa Data Quality and SAP Information Steward based on real PeerSpot user reviews.
Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality."The customers' addresses are now complete, correct and follow one consistent format."
"Address parsing. Our other software does not have this functionality."
"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."
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."
"Standardizing allows me to more effectively check for duplicate/existing records. Verifying increases the value of the data."
"Initial setup was fairly straightforward. The documentation was very good in terms of how to integrate and consume the service(s) that we use. It did not take an abundance of time to set up things on our side to use the service."
"Our customer database is now significantly more accurate and reliable."
"Ability to keep our data set clean and usable for our community searches."
"The most valuable features are data quality insight, metadata management, and metadata dictionary."
"The solution is very fast."
"The data profiling was excellent, as was the ease of generating the dashboards."
"Setup is straightforward."
"The scorecard will highlight the percentage of good data and ensure the user can feel confident that the data is accurate within predetermined limits."
"Data insight is the most valuable feature."
"Initial setup was straightforward."
"The Data Cleansing and the scorecard dashboard are very valuable. Additionally, the financial aspect of SAP Information Steward is very good. When a rule is incorrect then it will show how much is it costing the business. These features are very valuable."
"There are some companies out there using Google or other sources to check / confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."
"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."
"It will mix up family members at times, so we will change addresses at times that shouldn’t be changed."
"The SSIS component setup seems a little klunky."
"One thing I would want to have, when you're doing a property search, you can do it either on the FIPS in the APN number or the address itself. For some entries, I'll have the APN number, and some I'll have the address. Apparently it cannot process something when both the FIPS-APN and the address are on there. I have to sort, once with one and once with the other, which is a little bit of a pain."
"Pricing model."
"Address validation and parsing in a few countries have room for improvement."
"One of the problems that we ran into this year was we probably spent over 40 hours finding and trying to drill down to where specific bugs were in the program, which was a tremendous waste of time for us. There were a couple of updates to Windows this year, the program kept crashing. It happened on two different occasions over a period of a few months. Once we told them what the problem was - even though their tech support is great to work with - it literally took probably about two months to fix the issue where we could actually use the program the way we needed to use it."
"Needs to be more powerful on rules."
"The support team is not very responsive."
"The solution could improve by incorporating other applications, such as Power BI to show more visualization. More interaction with other solutions would be a good benefit."
"Performance could be improved."
"We'd like to see some manipulation techniques included in SAP Information Steward."
"A problem with the solution is that it does not allow us to review the results of Information Stewards for other analogies."
"The user experience of metapedia could be improved."
"Granularity could be reduced from an application level to the object level."
Earn 20 points
Melissa Data Quality is ranked 9th in Data Quality with 40 reviews while SAP Information Steward is ranked 6th in Data Quality with 9 reviews. Melissa Data Quality is rated 8.4, while SAP Information Steward is rated 7.6. The top reviewer of Melissa Data Quality writes "SSIS MatchUp Component is Amazing". On the other hand, the top reviewer of SAP Information Steward writes "Great for collecting, monitoring and planning storage capacity; functionality could be improved". Melissa Data Quality is most compared with Informatica Address Verification, SAP Data Quality Management, Precisely Trillium and Experian Data Quality, whereas SAP Information Steward is most compared with SAP Data Quality Management, SAP Data Services, Innovative Systems iLytics Enterprise Data Quality, SAP PowerDesigner and Syniti Information Management.
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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.
