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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 (3rd)
SAP Information Steward
Ranking in Data Quality
10th
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Metadata Management (6th)
 

Mindshare comparison

As of June 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 3.1%, up from 2.7% compared to the previous year. The mindshare of SAP Information Steward is 3.2%, 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

"​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."
"We are able to send out client mailings with the most accurate addresses possible."
"​Ability to keep our data set clean and usable for our community searches.​"
"Services for all manner of data-driven organizations, no matter their size or budget."
"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."
"It cuts down significantly on time in trying to match names to addresses. I can do in a few hours what would otherwise take days to accomplish."
"Be confident that the scalability and load are not going to be an issue with the services. ​"
"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."
"The most valuable features are data quality insight, metadata management, and metadata dictionary."
"Ability to collect information, monitor user access and to plan storage capacity."
"Initial setup was straightforward."
"Data insight is the most valuable feature."
"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."
 

Cons

"The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed"
"Pricing is based on tiers, with each tier capped at a specified number of records processed. Once you go over the cap at one tier, you are automatically bumped to the next tier. However, they seem to count failed batch processes so it’s good to keep track of the number of records sent. They’ll fix the count when notified, but their system fails to detect actual successful processes versus failed processes."
"We encounter failed batch processes once in a while, but their team is quick to rectify issues."
"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."
"The SSIS component setup seems a little klunky."
"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."
"Pricing model."
"It would be nice if it also had a user interface, as it did in years past."
"A problem with the solution is that it does not allow us to review the results of Information Stewards for other analogies."
"Needs to be more powerful on rules."
"The user experience of metapedia could be improved."
"Granularity could be reduced from an application level to the object level."
"Performance could be improved."
"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."
"SAP Information Steward could be improved by offering a cloud version of the product."
 

Pricing and Cost Advice

"Fully understand your volume, both monthly and annually. Speak with a Melissa account manager, they will put together an effective solution to meet your needs."
"They were willing to work with our preferred vendors, though it involved extra steps to get the license."
"This vendor has no equal in pricing for equivalent functionality."
"Understand how may transactions you will be processing so that you can get the right tier pricing."
"Cloud version is very cheap. On-premise version is expensive."
"​You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle.​"
"​It is affordable."
"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."
"SAP Information Steward is an expensive solution compared to others."
"Smaller-sized organizations may not be able to invest in SAP Information Steward because of the cost."
"I do not know if there were additional costs beyond the standard licensing fees."
"A bit pricey, and better tools are available for a lower price."
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Top Industries

By visitors reading reviews
Insurance Company
15%
Manufacturing Company
12%
Financial Services Firm
11%
Computer Software Company
10%
Manufacturing Company
21%
Financial Services Firm
14%
Government
14%
Computer Software Company
10%
 

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: June 2025.
859,129 professionals have used our research since 2012.