Try our new research platform with insights from 80,000+ expert users

Melissa Data Quality vs SAP Information Steward 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 Information Steward
Ranking in Data Quality
9th
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Metadata Management (6th)
 

Mindshare comparison

As of May 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 3.0%, up from 2.9% compared to the previous year. The mindshare of SAP Information Steward is 3.4%, down from 4.6% 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.
FranciscoSantos - PeerSpot reviewer
Provides accurate data that is validated against a personalized reference tool
For most SAP customers, Information Steward is enough because it is able to build quality data rules to detect issues in the source systems like SAP HANA, Business Warehouse, or other systems. A business user can first organize their data into several data domains. For example, procurement, human resources, and logistics setup. The domains can build data quality dimensions where you can describe the kind of rule that you are going to use. The user then can immediately see if something is wrong with their data using traffic lights. Another great feature of SAP Information Steward is the accuracy that the content is followed by validating against the reference tool. With the solution, you are creating data quality dimensions. Within these dimensions, you are creating business data quality rules that are looking for specific fields. From these rules, you can create a scorecard. The scorecard will highlight the percentage of good data and ensure the user can feel confident that the data is accurate within predetermined limits. SAP tables have field names that are very cryptic, making them hard to understand the meaning of the fields. Metapedia helps describe these fields in business terms.

Quotes from Members

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

Pros

"​We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database.​"
"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."
"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."
"There have been tangible benefits in combating fraudulent transactions. The information from Melissa Data is fed straight into our fraud system. This creates efficiency but also removes the need for manual address checks."
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information."
"By using Melissa Data, we are able to scrub and verify, then better validate the end customer's address to ensure a more consistent delivery of products."
"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."
"The most valuable features are data quality insight, metadata management, and metadata dictionary."
"Initial setup was straightforward."
"Setup is straightforward."
"The solution is very fast."
"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."
"Data insight is the most valuable feature."
"The scorecard will highlight the percentage of good data and ensure the user can feel confident that the data is accurate within predetermined limits."
"The data profiling was excellent, as was the ease of generating the dashboards."
 

Cons

"Needs to provide more phone numbers, even cell numbers (scrubbed numbers)."
"Pricing model."
"Address validation and parsing in a few countries have room for improvement."
"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.""
"Needs to validate more addresses accurately."
"Many issues, sometimes I have to completely log out and start over."
"Needs more/better search tools are needed. Also, state and local tax data would be nice."
"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."
"SAP Information Steward could be improved by offering a cloud version of the product."
"We'd like to see some manipulation techniques included in SAP Information Steward."
"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."
"The user experience of metapedia could be improved."
"Granularity could be reduced from an application level to the object level."
"Needs to be more powerful on rules."
"Performance could be improved."
 

Pricing and Cost Advice

"I think it's worth the value for me to run it."
"Depends on situation. We prefer to have data onsite, but some might prefer web access."
"Trial subscriptions (via cloud) are very cheap and easy to use. It’s a great way to test Listware to see if you want to go deeper with integration."
"It's affordable."
"Pricing is very reasonable."
"They were willing to work with our preferred vendors, though it involved extra steps to get the license."
"​It is affordable."
"Melissa pricing is competitive."
"Smaller-sized organizations may not be able to invest in SAP Information Steward because of the cost."
"A bit pricey, and better tools are available for a lower price."
"I do not know if there were additional costs beyond the standard licensing fees."
"SAP Information Steward is an expensive solution compared to others."
report
Use our free recommendation engine to learn which Data Quality solutions are best for your needs.
850,028 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Insurance Company
15%
Manufacturing Company
12%
Financial Services Firm
11%
Computer Software Company
10%
Manufacturing Company
22%
Financial Services Firm
16%
Government
13%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Also Known As

No data available
Information Steward, SAP Data Insight
 

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.
American Water, Graphic Packaging International, OSRAM Licht AG, Maxim Integrated
Find out what your peers are saying about Melissa Data Quality vs. SAP Information Steward and other solutions. Updated: April 2025.
850,028 professionals have used our research since 2012.