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Melissa Data Quality vs SAP Data Quality Management comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 6, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Melissa Data Quality
Ranking in Data Quality
8th
Average Rating
8.4
Reviews Sentiment
7.6
Number of Reviews
40
Ranking in other categories
Data Scrubbing Software (4th)
SAP Data Quality Management
Ranking in Data Quality
10th
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 2.7%, down from 3.2% compared to the previous year. The mindshare of SAP Data Quality Management is 4.4%, down from 6.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality
 

Featured Reviews

GM
SSIS MatchUp Component is Amazing
- Scalability is a limitation as it is single threaded. You can bypass this limitation by partitioning your data (say by alphabetic ranges) into multiple dataflows but even within a single dataflow the tool starts to really bog down if you are doing survivorship on a lot of columns. It's just very old technology written that's starting to show its age since it's been fundamentally the same for many years. To stay relavent they will need to replace it with either ADF or SSIS-IR compliant version. - Licensing could be greatly simplified. As soon as a license expires (which is specific to each server) the product stops functioning without prior notice and requires a new license by contacting the vendor. And updating the license is overly complicated. - The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation but that isn't true since pretty much all SSIS components are resizable except theirs! This is just an annoyance but needless impact on productivity when developing new data flows. - The tool needs to provide for incremental matching using the MatchUp for SSIS tool (they provide this for other solutions such as standalone tool and MatchUp web service). We had to code our own incremental logic to work around this. - Tool needs ability to sort mapped columns in the GUI when using advanced survivorship (only allowed when not using column-level survivorship). - It should provide an option for a procedural language (such as C# or VB) for survivor-ship expressions rather than relying on SSIS expression language. - It should provide a more sophisticated ability to concatenate groups of data fields into common blocks of data for advanced survivor-ship prioritization (we do most of this in SQL prior to feeding the data to the tool). - It should provide the ability to only do survivor-ship with no matching (matching is currently required when running data through the tool). - Tool should provide a component similar to BDD to enable the ability to split into multiple thread matches based on data partitions for matching and survivor-ship rather than requiring custom coding a parallel capable solution. We broke down customer data by first letter of last name into ranges of last names so we could run parallel data flows. - Documentation needs to be provided that is specific to MatchUp for SSIS. Most of their wiki pages were written for the web service API MatchUp Object rather than the SSIS component. - They need to update their wiki site documentation as much of it is not kept current. Its also very very basic offering very little in terms of guidelines. For example, the tool is single-threaded so getting great performance requires running multiple parallel data flows or BDD in a data flow which you can figure out on your own but many SSIS practitioners aren't familiar with those techniques. - The tool can hang or crash on rare occasions for unknown reason. Restarting the package resolves the problem. I suspect they have something to do with running on VM (vendor doesn't recommend running on VM) but have no evidence to support it. When it crashes it creates dump file with just vague message saying the executable stopped running.
Rene Dorantes - PeerSpot reviewer
Scalable, stable, and offers good technical support
SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management. What I'd like to see from SAP Data Quality Management in the future is the integration of machines on the shop floor or a feature that connects shop floor devices. I'd also like a custom dashboard in the solution, though I wonder if that's available in the new version. The old version my company uses doesn't have that. Another feature I want in the next release of SAP Data Quality Management is better communication between the ME and the SAP systems.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"​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."
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."
"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 mainly communicate with our customers via email, so we primarily use it to find a phone number so we can contact them more efficiently. This allows us to talk to them and resolve their issues much more quickly."
"Getting the most up to date address for our members. We like to keep in touch with membership a few times a year so we want to maintain up to date addresses to be sure they receive any information that we mail to them."
"​It has a straightforward, easy setup."
"We use a Melissa API to access the data, so it easy to use, accurate, and fast."
"Provides quality accurate data that our downstream solutions depend on."
"We work with API standards or norms for internal applications, so it's essential for SSE to have tests and pass those tests according to the criteria, which makes SAP Data Quality Management very important for our products."
"Our primary use case is for us to inspect the results from the product and material, and for releasing or leaving the status of the product."
 

Cons

"We have noticed that some of the emails and addresses return with confusing or incorrect codes, but for the most part, it is accurate.​"
"We encounter failed batch processes once in a while, but their team is quick to rectify issues."
"The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation however all SSIS components are resizable so that isn't true. This is just an annoyance but needless."
"Needs to validate more addresses accurately."
"Did not work as advertized. Needs better results in address parsing, as described on the website."
"I wish there was a way to do a "test run" and see what a particular format will give you."
"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."
"I would like for them to develop a feature to able to record all of our inspections; so all the data can go through SAP. It's not user-friendly or easy to get further analysis, so we mostly skip this step."
"SAP Data Quality Management would be better if it directly integrates with the ME system. Right now, the company has a lot of machines on the shop floor working as a standalone, so you have to use all methods to ensure that the data interface appears on the ME system and that SAP Data Quality Management records the QM results. It would be much easier if the ME system could be integrated directly with SAP Data Quality Management."
 

Pricing and Cost Advice

"It's affordable."
"This vendor has no equal in pricing for equivalent functionality."
"Depends on situation. We prefer to have data onsite, but some might prefer web access."
"Pricing is very reasonable."
"​It is affordable."
"The only complaint that I have towards it is they sell licenses based on a range of usage, and I feel those ranges are too large."
"The price for address validation is similar in all software. However, the price for geocoding decides the actual pricing. If you get their most accurate geocoding (called GeoPoints), then it will add about $10k+ per million requests."
"Understand how may transactions you will be processing so that you can get the right tier pricing."
Information not available
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Top Industries

By visitors reading reviews
Manufacturing Company
15%
Insurance Company
14%
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
16%
Financial Services Firm
16%
Computer Software Company
15%
Energy/Utilities Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Also Known As

No data available
SAP BusinessObjects Data Quality Management, BusinessObjects Data Quality Management
 

Overview

 

Sample Customers

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.
AOK Bundesverband, Surgutneftegas Open Joint Stock Company, Molson Coors Brewing Company, City of Buenos Aires, ASR Group, Citrix, EarlySense, Usha International Limited, Automotive Resources International, Wªrth Group, Takisada-Osaka Co. Ltd., Coelba, R
Find out what your peers are saying about Melissa Data Quality vs. SAP Data Quality Management and other solutions. Updated: January 2025.
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