Melissa Data Quality vs WinPure Data Quality Platform comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between Melissa Data Quality and WinPure Data Quality Platform based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality.
To learn more, read our detailed Data Quality Report (Updated: May 2024).
772,127 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Address verification ensures our customers get their packages, and we aren’t charged for incomplete address information.""Gives us the ability to offer an additional resource that other companies do not.""​It has a straightforward, easy setup.""We use a Melissa API to access the data, so it easy to use, accurate, and fast.""SSIS integration.""​We are able to more accurately identify valid, and better formatted, data which improves the data we store in our database.​""We use their GeoPoints to get the most precise, rooftop level geocoding.""This tool works better for us than using a batch processing system that we do not have enough control over as each record is being processed."

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"With regards to choosing flash versus traditional storage, it's just so much simpler to manage and users get so much better performance from flash."

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Cons
"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.""The SSIS component setup seems a little klunky.""​If I had multiple Excel files open and ran Listware it would crash Excel, charge the credits, and not save the results.""It could always be cheaper.""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."

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"The pricing model could use improvement."

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Pricing and Cost Advice
  • "It's affordable."
  • "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."
  • "They were willing to work with our preferred vendors, though it involved extra steps to get the license."
  • "Depends on situation. We prefer to have data onsite, but some might prefer web access."
  • "Melissa pricing is competitive."
  • "Pricing is very reasonable."
  • "I think it's worth the value for me to run it."
  • "Generally, the cost is ROI positive, depending on your shipping volume."
  • More Melissa Data Quality Pricing and Cost Advice →

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    Ranking
    9th
    out of 44 in Data Quality
    Views
    623
    Comparisons
    345
    Reviews
    1
    Average Words per Review
    2,004
    Rating
    9.0
    Unranked
    In Data Quality
    Comparisons
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    WinPure
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    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.

    Winpure Data Cleaning Matrix provides a method of applying a whole host of cleaning processes onto your data. Containing an array of tools to help clean, correct, standardize and transform your data the matrix is divided into 7 sections, each section focusing on a specific data cleaning operation. All settings can then be stored and used on other similar data sets thus saving a lot of time.

    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.
    Birmingham Hippodrome, Luton Borough Council, Apex Innovations, Sandia National Laboratories, Clear Blue, Vodafone
    Top Industries
    REVIEWERS
    Healthcare Company16%
    Retailer11%
    Financial Services Firm11%
    Government11%
    VISITORS READING REVIEWS
    Manufacturing Company13%
    Computer Software Company12%
    Financial Services Firm11%
    Government10%
    No Data Available
    Company Size
    REVIEWERS
    Small Business41%
    Midsize Enterprise10%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business24%
    Midsize Enterprise17%
    Large Enterprise58%
    No Data Available
    Buyer's Guide
    Data Quality
    May 2024
    Find out what your peers are saying about Informatica, SAP, Talend and others in Data Quality. Updated: May 2024.
    772,127 professionals have used our research since 2012.

    Melissa Data Quality is ranked 9th in Data Quality with 40 reviews while WinPure Data Quality Platform doesn't meet the minimum requirements to be ranked in Data Quality. Melissa Data Quality is rated 8.4, while WinPure Data Quality Platform is rated 0.0. The top reviewer of Melissa Data Quality writes "SSIS MatchUp Component is Amazing". On the other hand, the top reviewer of WinPure Data Quality Platform writes "A solution that offers good performance, good stability, and a straightforward setup". Melissa Data Quality is most compared with Informatica Address Verification, SAP Data Quality Management, Precisely Trillium and Experian Data Quality, whereas WinPure Data Quality Platform is most compared with .

    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.