Melissa Data Quality vs SAS Data Management comparison

Melissa and SAS are both solutions in the Data Quality category. Melissa is ranked #8 with an average rating of 9.0, while SAS is ranked #11 with an average rating of 7.5. Melissa holds a 2.8% mindshare in DQ, compared to SAS’s 2.2% mindshare. Additionally, 95% of Melissa users are willing to recommend the solution, compared to 87% of SAS users who would recommend it.

Melissa Data Quality

Read 40 Melissa Data Quality reviews

436 Views
229 Comparison Views

95% willing to recommend

SAS Data Management

Read 16 SAS Data Management reviews

211 Views
175 Comparison Views

87% willing to recommend

Melissa Data Quality

SAS Data Management

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Executive SummaryUpdated on Jan 6, 2025

SAS Data Management and Melissa Data Quality compete in the data management and quality sector. Melissa Data Quality is often regarded as superior due to its feature robustness, despite SAS's strong support and pricing.

Features: SAS Data Management provides robust data integration, powerful analytics tools, and strong governance capabilities. Melissa Data Quality focuses on data verification, enrichment, and cleansing, offering advanced data cleansing features.

Room for Improvement: SAS Data Management could enhance user interface intuitiveness, expand cloud compatibility, and streamline complex customization options. Melissa Data Quality could benefit from a wider range of integration options, enhanced real-time processing, and more comprehensive support for international data standards.

Ease of Deployment and Customer Service: SAS Data Management offers comprehensive deployment options with responsive customer support, ensuring a seamless setup process. Melissa Data Quality emphasizes streamlined deployment and efficient customer service, providing ease and quick access to support.

Pricing and ROI: SAS Data Management involves higher initial costs but offers significant ROI through its broad functionalities. Melissa Data Quality generally has a lower entry cost with quick ROI due to its focused data quality improvements, making it cost-effective for many businesses.

To learn more, read our detailed Melissa Data Quality vs. SAS Data Management Report (Updated: April 2025).

Buyer's Guide

Melissa Data Quality vs. SAS Data Management

April 2025

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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

Ranking in other categories

Data Scrubbing Software (4th)

SAS Data Management

Ranking in Data Quality

11th

Average Rating

8.4

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Integration (35th), Data Governance (26th)

Mindshare comparison

As of April 2025, in the Data Quality category, the mindshare of Melissa Data Quality is 2.8%, down from 3.0% compared to the previous year. The mindshare of SAS Data Management is 2.2%, up from 2.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality

Featured Reviews

GaryM

Data Architect at World Vision

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.

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Vivek Trivedi

Head finance transformation at Ahli United Bank Ksc

Has robust data governance capabilities and efficient financial alerting features

The platform's robust data governance capabilities ensure strong compliance with regulatory standards. Our dedicated data governance team is responsible for setting policies and monitoring data access and usage. Additionally, we have a Data Protection Officer (DPO) and an independent InfoSec team that work together to enforce these policies. This multi-layered approach ensures that data governance is effectively managed and compliant with all necessary regulations. It is integrated with SQL and Power BI servers for executive management dashboard reporting. This integration supports comprehensive data analysis and reporting needs, which was a key factor in our decision. The value of using vCenter lies in its comprehensive data infrastructure management. It significantly enhances our reporting, day-to-day decision-making, and analytics capabilities. Integrating SaaS with vCenter adds value by streamlining key functions and improving overall organizational efficiency. The solution can be considered expensive, particularly due to infrastructure, maintenance, and ownership costs. The long-term savings and efficiencies gained from using vCenter can justify the investment for large organizations. However, the high costs might not be justifiable for smaller organizations with less data and fewer resources. Conducting a thorough cost-benefit analysis based on the organization's specific needs and scale is recommended. I rate it an eight.

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Quotes from Members

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

Pros

"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."

"We like having the ability to write our own utilities/software to process our records and store the final output the way we want."

"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."

"It gives me an assessed value of the property in question. My partner and I are property investors, and it's good to get an assessed value to cull out properties that we're not interested in."

"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."

"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."

"Extremely easy to install and setup."

More Melissa Data Quality pros

"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."

"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."

"The platform's robust data governance capabilities ensure strong compliance with regulatory standards."

"I am impressed with the tool's ability to customize."

"The tool is reliable, quick, and powerful."

"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."

"The technical support is excellent."

"The product offers very good flexibility."

More SAS Data Management pros

Cons

"MatchUp seems to be single threaded, and limits the amount of data that can be processed automatically."

"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."

"To continually update the database with NAICS codes on businesses."

"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."

"Did not work as advertized. Needs better results in address parsing, as described on the website."

"It would be nice if it also had a user interface, as it did in years past."

"MatchUp is a more complex product and I recommend a test area before upgrading to production. Performance can change from version to version."

"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.""

More Melissa Data Quality cons

"The solution is quite expensive and hard to install/configure."

"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."

"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."

"The pricing of the solution needs to be improved. They need to work to make it more affordable."

"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."

"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."

"The solution could use better documentation."

"Integration and cloud migration are areas where we see potential for improvement."

More SAS Data Management cons

Pricing and Cost Advice

"I think it's worth the value for me to run it."

"We are concerned that our own pricing is going up every year for Melissa Data products, but we highly recommend the services for people who are routinely sending out mailings."

"Cloud version is very cheap. On-premise version is expensive."

"Understand how may transactions you will be processing so that you can get the right tier pricing."

"Melissa pricing is competitive."

"Buy a lot more credits than you think you’re going to need."

"Be sure to determine how the data is priced (record-based versus credit-based or some hybrid of data and services)."

"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."

More Melissa Data Quality pricing and cost advice

"The tool is a bit expensive."

"While it is even free for personal use on the cloud, it can be expensive for desktop installations and enterprise use."

"The solution is expensive."

"The licensing model for vCenter is a perpetual license with yearly payments."

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Top Industries

By visitors reading reviews

Insurance Company

15%

Manufacturing Company

12%

Financial Services Firm

11%

Computer Software Company

Financial Services Firm

29%

Computer Software Company

12%

Insurance Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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What do you like most about SAS Data Management?

I am impressed with the tool's ability to customize.

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What is your experience regarding pricing and costs for SAS Data Management?

The licensing model for vCenter is a perpetual license with yearly payments. This model ensures continuous updates and support while managing initial setup costs.

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What needs improvement with SAS Data Management?

Integration and cloud migration are areas where we see potential for improvement. A more seamless integration process and transitioning to a cloud-based environment would enhance user-friendliness ...

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Comparisons

Experian Data Quality vs Melissa Data Quality

Compared 40% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Melissa Data Quality

Compared 36% of the time

Talend Data Quality vs Melissa Data Quality

Compared 23% of the time

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Informatica Intelligent Data Management Cloud (IDMC) vs SAS Data Management

Compared 20% of the time

Palantir Foundry vs SAS Data Management

Compared 17% of the time

Informatica PowerCenter vs SAS Data Management

Compared 14% of the time

Collibra Governance vs SAS Data Management

Compared 12% of the time

Talend Open Studio vs SAS Data Management

Compared 10% of the time

More SAS Data Management Competitors

Product Reports

Buyer's Guide

Melissa Data Quality

March 2025

Download Melissa Data Quality product report

Buyer's Guide

SAS Data Management

March 2025

Download SAS Data Management product report

Also Known As

No data available

SAS Data Management Platform, Data Management Platform, DataFlux

Overview

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Melissa

Every decision, every business move, every successful customer interaction - they all come down to high-quality, well-integrated data. If you don't have it, you don't win. SAS Data Management is an industry-leading solution built on a data quality platform that helps you improve, integrate and govern your data.

SAS

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.

Data Management, 1-800-FLOWERS.COM, Absa, Aegon, Allianz Global Corporate & SpecialtyAusgrid, Bank of Queensland, Bell, BMC Software, Canada Post, Ceska pojistovna, Chantecler, Chubb Group of Insurance Companies, Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Enerjisa, ERGO Insurance Group, Florida Department of Corrections, Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, North Carolina Office of Information Technology Services, Orlando Magic, OTP Group, PITT OHIO, Plano Independent School District, RWE Poland, Spanish Air Force, Stockholm County Council, Telus, The Travel Corporation, Transitions Optical, Triad Analytic Solutions, UNIQA, US Census Bureau, US Department of Housing and Urban Development, USDA National Agricultural Statistics Service, West Midlands Police, XS Inc., Zenith Insurance

Buyer's Guide

Melissa Data Quality vs. SAS Data Management

April 2025

Free Report: Melissa Data Quality vs. SAS Data Management

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