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IBM InfoSphere Information Server vs. Melissa Data Quality Suite

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM InfoSphere Information Server

    Score10 out of 10
    N/AIBM InfoSphere Information Server is a data integration platform used to understand, cleanse, monitor and transform data. The offerings provide massively parallel processing (MPP) capabilities.N/A

    Melissa Data Quality Suite

    Score9.1 out of 10
    N/AMelissa Data Quality Suite standardizes, verifies and corrects contact data including postal addresses, email addresses, phone numbers, and names. With flexible deployment through cloud web services or on-premise APIs, it validates addresses for 250 countries globally.N/A
    Pricing
    IBM InfoSphere Information ServerMelissa Data Quality Suite
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM InfoSphere Information ServerMelissa Data Quality Suite
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional DetailsData Quality Suite - Starting at $12,300.00 Per Year •1,000,000 Records/Year •On Premise – US & Canada •Email Validation, Autocomplete, Data Cleansing including Geolocation •Validate Non-USPS addresses •120-Day ROI Guarantee •Unlimited Tech Support •VIP Onboarding Development and Integration Support
    More Pricing Information
    Features
    IBM InfoSphere Information ServerMelissa Data Quality Suite
    Data Source Connection
    Comparison of Data Source Connection features of IBM InfoSphere Information Server and Melissa Data Quality Suite
    Feature
    IBM InfoSphere Information Server
    8.7
    4 Ratings
    4% above category average
    Melissa Data Quality Suite
    -
    Ratings
    Connect to traditional data sources9.94 Ratings00 Ratings
    Connecto to Big Data and NoSQL7.54 Ratings00 Ratings
    Data Transformations
    Comparison of Data Transformations features of IBM InfoSphere Information Server and Melissa Data Quality Suite
    Feature
    IBM InfoSphere Information Server
    9.6
    4 Ratings
    17% above category average
    Melissa Data Quality Suite
    -
    Ratings
    Simple transformations10.04 Ratings00 Ratings
    Complex transformations9.24 Ratings00 Ratings
    Data Modeling
    Comparison of Data Modeling features of IBM InfoSphere Information Server and Melissa Data Quality Suite
    Feature
    IBM InfoSphere Information Server
    8.0
    4 Ratings
    1% above category average
    Melissa Data Quality Suite
    -
    Ratings
    Data model creation8.72 Ratings00 Ratings
    Metadata management7.74 Ratings00 Ratings
    Business rules and workflow8.44 Ratings00 Ratings
    Collaboration8.04 Ratings00 Ratings
    Testing and debugging7.14 Ratings00 Ratings
    Data Governance
    Comparison of Data Governance features of IBM InfoSphere Information Server and Melissa Data Quality Suite
    Feature
    IBM InfoSphere Information Server
    9.7
    4 Ratings
    18% above category average
    Melissa Data Quality Suite
    -
    Ratings
    Integration with data quality tools10.04 Ratings00 Ratings
    Integration with MDM tools9.53 Ratings00 Ratings
    Data Quality
    Comparison of Data Quality features of IBM InfoSphere Information Server and Melissa Data Quality Suite
    Feature
    IBM InfoSphere Information Server
    -
    Ratings
    Melissa Data Quality Suite
    8.3
    1 Ratings
    3% below category average
    Data source connectivity00 Ratings8.01 Ratings
    Data profiling00 Ratings9.01 Ratings
    Master data management (MDM) integration00 Ratings8.01 Ratings
    Data element standardization00 Ratings8.01 Ratings
    Match and merge00 Ratings8.01 Ratings
    Address verification00 Ratings9.01 Ratings
    Best Alternatives
    IBM InfoSphere Information ServerMelissa Data Quality Suite
    Small Businesses
    Skyvia
    Score10 out of 10
    No answers on this topic
    Medium-sized Companies
    Informatica PowerCenter (legacy)
    Score9.3 out of 10
    No answers on this topic
    Enterprises
    SolarWinds Task Factory
    Score8.3 out of 10
    SAP Data Services
    Score7.8 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM InfoSphere Information ServerMelissa Data Quality Suite
    Likelihood to Recommend
    8.9
    (5 ratings)
    9.0
    (1 ratings)
    Likelihood to Renew
    8.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM InfoSphere Information ServerMelissa Data Quality Suite
    Likelihood to Recommend
    IBM
    Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.
    Read full review
    Melissa
    The platform is best suited for detailed exploration and filtering that allow users to examine the specific records
    that pass or fail a criterion and how they might relate to each other. It also assist in seeing past jobs and compare how quality has changed, providing
    more context than just point values.
    Incentivized
    Read full review
    Pros
    IBM
    • IIS best for ETL ,not ELT , and many and diffrent source systems.
    • It also can process big data , unstuctured data
    • It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems
    Incentivized
    Read full review
    Melissa
    • It provides ability to profile, discover, and validate data quality.
    • It allows to drill down into larger amounts of data.
    • It automatically suggests possible quality rules based on a statistical profile of the data.
    Incentivized
    Read full review
    Cons
    IBM
    • I would be nice to have a new web development environment for DataStage.
    • Connectivity Packs such as Pack for SAP Application are a little pricey.
    • It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.
    Incentivized
    Read full review
    Melissa
    • It can expand connectivity to apply adaptive data quality rules to any data source.
    • It can employing more advanced transformation techniques to transform data for specific formats.
    • It can further continue on its existing capabilities like providing more enriched data curation.
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    • Scale of implementation
    • IBM techsupport
    Incentivized
    Read full review
    Melissa
    No answers on this topic
    Alternatives Considered
    IBM
    DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS
    Read full review
    Melissa
    No answers on this topic
    Return on Investment
    IBM
    • Productivity of the development of integration processes.
    • Better documentation and governance.
    • Reduce training costs of various technologies.
    Read full review
    Melissa
    No answers on this topic
    ScreenShots

    Melissa Data Quality Suite Screenshots

    Screenshot of Email Verification: Verify email addresses and receive deliverability confidence score, result codes and domain informationScreenshot of Predictive Accept-All Validation: The Predictive Accept-All Validation feature offers a unique approach to evaluating emails hosted on accept-all servers. While these servers might typically mask inactive or invalid addresses, its proprietary algorithm analyzes patterns and traces of historical activity, giving users a reliable window into the likelihood of successful delivery.Screenshot of Domain Correction: Utilizes state-of-the-art fuzzy matching and data correlation algorithms to automatically correct misspelled domains and outdated providers. Global Email will validate the corrected and standardized version of the input email. By identifying and fixing typos like “dmail.com” to “gmail.com” prior to validation, the system ensures that each email address is accurate before it’s verified, leading to better results and enhanced mailing listsScreenshot of Melissa vs. Other Email Verification ProvidersScreenshot of Phone Verification: Verify any U.S., Canadian, or international telephone numberScreenshot of Phone Verification Step 1: Input- Validates a phone number at point of entry so bad data never enters your system.