Magic Quadrant for Data Quality Tools 9 June 2009

Ted Friedman, Andreas Bitterer

Gartner RAS Core Research Note G00167657

The data quality tools market continues to grow despite economic conditions, as organizations invest in master datamanagement and information governance. Vendors and buyers are pursuing innovations to improve support forbusiness-facing roles and increase the pervasiveness of data quality controls.

What You Need to Know

This document was revised on 23 June 2009. For more information,see the Corrections page on gartner.com.

The market for data quality tools continues to enjoy significant growthdespite challenging economic conditions and the general curtailment of ITbudgets. Organizations are aware that data quality competence isfundamental to the success of critical initiatives such as master datamanagement (MDM), information governance, business intelligence (BI) andIT modernization. This awareness has increased the demand for insightabout best practices, organizational structures and technology to supportthe data quality discipline. The vendor landscape has remained fairly stableduring the past twelve months, although a number of new, smaller startupsand specialist providers have emerged. The market remains divided into acluster of leaders with broad functionality, large customer bases and a fairlycomprehensive market vision; and a range of challengers, visionaries andniche players that tend to have limited vision and/or scale. The trend ofconvergence of the data quality tools market with related markets for dataintegration tools and MDM products continues, as organizations recognizethat they must ensure the quality of the data being delivered in their dataintegration architectures, and the data that persists in their master datarepositories. This is reflected in the vendor landscape, with a rapidlygrowing number of providers competing in more than one of these currentlydiscrete markets.

When evaluating offerings in this market, organizations must consider notonly the breadth of functional capabilities (for example, data profiling,parsing, standardization, matching, monitoring and enrichment) relative totheir requirements, but also the degree to which this functionality can bereadily understood, managed and leveraged by non-IT resources. In keepingwith significant trends in data management, business roles such as datastewards will increasingly be responsible for managing the goals, rules,processes and metrics associated with data quality improvement initiatives.Other key considerations include the degree of integration of the range offunctional capabilities into a single architecture and product, and theavailable deployment options (traditional on-premises software deployment,hosted solutions and software as a service [SaaS]). Finally, given thecurrent economic and market conditions, buyers must deeply analyzenon-technology characteristics, such as pricing models and total costfootprint, as well as the size, viability and partnerships of the vendors.

Use this Magic Quadrant to understand the data quality tools market and

Acronym Key and Glossary Terms

BI business intelligence

CDQ Customer Data Quality

ETL extraction, transformation andloading

ISV independent software vendor

MDM master data management

SaaS software as a service

SI system integrator

SOA service-oriented architecture

UDC Universal Data Cleanse

VAR value-added reseller

Vendors Added or Dropped

We review and adjust our inclusion criteria forMagic Quadrants and MarketScopes as marketschange. As a result of these adjustments, themix of vendors in any Magic Quadrant orMarketScope may change over time. A vendorappearing in a Magic Quadrant or MarketScopeone year and not the next does not necessarilyindicate that we have changed our opinion ofthat vendor. This may be a reflection of achange in the market and, therefore, changedevaluation criteria, or a change of focus by avendor.

Evaluation Criteria Definitions

Ability to Execute

Product/Service: Core goods and servicesoffered by the vendor that compete in/serve thedefined market. This includes currentproduct/service capabilities, quality, feature sets,skills, etc., whether offered natively or throughOEM agreements/partnerships as defined in themarket definition and detailed in the subcriteria.

Overall Viability (Business Unit, Financial,Strategy, Organization): Viability includes anassessment of the overall organization's financialhealth, the financial and practical success of the

how Gartner rates the leading vendors and their packaged products in thatmarket. Draw on this research to evaluate vendors based on a customizedset of objective criteria. Gartner advises organizations against simplyselecting vendors in the Leaders quadrant. All selections are buyer-specific,and vendors from the Challengers, Niche Players or Visionaries quadrantscould be better matches for your requirements.

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Magic Quadrant

Figure 1. Magic Quadrant for Data Quality Tools

Source: Gartner (June 2009)

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Market Overview

Organizations of all sizes and in all industries are recognizing theimportance of high-quality data and the critical role of data quality ininformation governance and stewardship, driven by broader enterpriseinformation management initiatives. As a result, their interest in the role oftools and technology for data quality improvement continues to grow.Fueled by a market of purpose-built, packaged tools for addressing variousdimensions of the data quality discipline, data quality functionality is readilyavailable from a variety of providers, both large and small. Data qualityfunctionality is also being recognized as a fundamental component ofofferings in many related software markets, such as data integration tools,MDM solutions and BI platforms. As a result, an increasing number ofpartnerships between MDM solution vendors and data quality tools vendorsare occurring, as the desire for stronger matching, standardization andcleansing functionality for MDM grows. In addition, there is an increase inthe usage of data quality tools to support custom-developed MDMarchitectures in many organizations.

The vendors in this market offer a broad range of data quality functionality,ranging from data quality analysis, profiling and monitoring, to datacleansing operations such as parsing, standardization and matching,through to data enrichment. Much convergence and integration oftechnology has occurred, and today vendors offer more functionality withina smaller number of discrete products — most vendors have consolidatedthe bulk of their core data quality functionality into a single data quality

business unit, and the likelihood of the individualbusiness unit to continue investing in theproduct, to continue offering the product and toadvance the state of the art within theorganization's portfolio of products.

Sales Execution/Pricing: The vendor’scapabilities in all pre-sales activities and thestructure that supports them. This includes dealmanagement, pricing and negotiation, pre-salessupport and the overall effectiveness of thesales channel.

Market Responsiveness and Track Record:Ability to respond, change direction, be flexibleand achieve competitive success asopportunities develop, competitors act,customer needs evolve and market dynamicschange. This criterion also considers thevendor's history of responsiveness.

Marketing Execution: The clarity, quality,creativity and efficacy of programs designed todeliver the organization's message to influencethe market, promote the brand and business,increase awareness of the products, andestablish a positive identification with theproduct/brand and organization in the minds ofbuyers. This "mind share" can be driven by acombination of publicity, promotional, thoughtleadership, word-of-mouth and sales activities.

Customer Experience: Relationships, productsand services/programs that enable clients to besuccessful with the products evaluated.Specifically, this includes the ways customersreceive technical support or account support.This can also include ancillary tools, customersupport programs (and the quality thereof),availability of user groups, service-levelagreements, etc.

Operations: The ability of the organization tomeet its goals and commitments. Factors includethe quality of the organizational structureincluding skills, experiences, programs, systemsand other vehicles that enable the organizationto operate effectively and efficiently on anongoing basis.

Completeness of Vision

Market Understanding: Ability of the vendorto understand buyers' wants and needs and totranslate those into products and services.Vendors that show the highest degree of visionlisten and understand buyers' wants and needs,and can shape or enhance those with theiradded vision.

Marketing Strategy: A clear, differentiated setof messages consistently communicatedthroughout the organization and externalizedthrough the Web site, advertising, customerprograms and positioning statements.

Sales Strategy: The strategy for selling productthat uses the appropriate network of direct andindirect sales, marketing, service andcommunication affiliates that extend the scopeand depth of market reach, skills, expertise,technologies, services and the customer base.

Offering (Product) Strategy: The vendor'sapproach to product development and deliverythat emphasizes differentiation, functionality,methodology and feature set as they map tocurrent and future requirements.

Business Model: The soundness and logic ofthe vendor's underlying business proposition.

Vertical/Industry Strategy: The vendor'sstrategy to direct resources, skills and offeringsto meet the specific needs of individual marketsegments, including verticals.

Innovation: Direct, related, complementary andsynergistic layouts of resources, expertise orcapital for investment, consolidation, defensiveor pre-emptive purposes.

Geographic Strategy: The vendor's strategyto direct resources, skills and offerings to meetthe specific needs of geographies outside the"home" or native geography, either directly orthrough partners, channels and subsidiaries asappropriate for that geography and market.

platform, with data profiling remaining the only major functional componentcommonly sold as a separate product. However, specialized add-oncapabilities (such as global name and address support, application-specificknowledge bases and dashboards for data quality metrics) persist for theircore platforms, and even grow in number, as vendors adapt their packagingand pricing models to suit a wider range of potential buyers.

One of the most significant trends in this market is the continued expansionof the tools' capabilities beyond the basic data quality operations of parsing,standardization and matching of structured data assets in a narrow set ofdata domains (for example, customer data only). Increasingly, both newentrants and longtime competitors are delivering technology with a focus ondata quality analysis, pervasive deployment of data quality controls,ongoing data quality monitoring and the flexibility to address a range ofdata subject areas.

The market for data quality tools is of moderate size (estimated at between$400 million and $500 million at the end of 2008), and during the next fewyears is expected to experience stronger growth than many other softwaremarkets. This is a result of the significant attention that organizations arefocusing on information governance (of which data quality assurance is asignificant component, and for which data quality tools provide support forfacilitating and executing information governance initiatives), and costoptimization (since data quality issues contribute to increased costs anddata quality tools can be leveraged to directly reduce inefficiencies andwaste by improving the productivity of people and the value of informationassets). Much of the innovation continues to come from outside the U.S. Asa result, the veteran data quality tool vendors are being challenged byentrants with a more significant international focus. Many new entrantsfocus on "domain-agnostic" data quality services (stand-alone or embeddedin applications), based on a centrally managed set of business rules.However, with the increasing trend toward embedding data qualitycapabilities in business applications, data integration tools and othersoftware offerings from larger vendors, these small competitors will facesignificant challenges as they attempt to survive and grow.

This market comprises a diverse set of vendors approaching the businessopportunity from different directions and backgrounds. Large applicationsand infrastructure technology providers, such as IBM and SAPBusinessObjects, increasingly focus on data quality capabilities ascomplementary to various components of their portfolios. While they selldata quality tools in a stand-alone manner (as individual products), thesetools are increasingly sold as part of a larger transaction involving relatedproducts (such as data integration tools and MDM solutions). Other largetechnology and services providers manage data quality-focused divisionssuch as SAS Institute (with its DataFlux subsidiary), Pitney Bowes (with itsBusiness Insight division) and Harte-Hanks (with its Trillium Softwaredivision). Specialists focused on data integration capabilities, such asInformatica (and other data integration tools vendors not directly positionedon the Data Quality Tools Magic Quadrant) have added data qualitycapabilities to their portfolios, either via acquisitions or organicdevelopment. This reflects the increasing overlap between the markets fordata integration tools and data quality tools. Finally, a large number ofpure-play specialist data quality tools vendors, including Datactics,DataLever, DataMentors, Datanomic, Human Inference, Innovative Systems,Netrics and Uniserv (and many others not positioned on the Magic Quadrantbecause they do not meet the inclusion criteria) vie for deals in stand-alonedata quality tools. Many of these specialists are small (with annual revenueof less than $100 million), and may be vulnerable to the challengingeconomic conditions and mounting competitive pressure from the largervendors.

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Market Definition/Description

The data quality tools market comprises vendors that offer stand-alonesoftware products to address the core functional requirements of the dataquality discipline:

Profiling. The analysis of data to capture statistics (metadata) thatprovide insight into the quality of the data and help to identify dataquality issues.

Parsing and standardization. The decomposition of text fields intocomponent parts and the formatting of values into consistent layoutsbased on industry standards, local standards (for example, postalauthority standards for address data), user-defined business rules andknowledge bases of values and patterns.Generalized "cleansing." The modification of data values to meetdomain restrictions, integrity constraints or other business rules thatdefine when the quality of data is sufficient for the organization.Matching. Identifying, linking or merging related entries within oracross sets of data.Monitoring. Deploying controls to ensure that data continues toconform to business rules that define data quality for theorganization.Enrichment. Enhancing the value of internally held data byappending related attributes from external sources (for example,consumer demographic attributes or geographic descriptors).

In addition, these products provide a range of related functional capabilitiesthat are not unique to this market but which are required to execute many ofthe data quality core functions, or for specific data quality applications:

Connectivity/adapters. The ability to interact with a range ofdifferent data structure types.Subject-area-specific support. Standardization capabilities forspecific data subject areas.International support. The relevance for data quality operations ona global basis.Metadata management. The ability to capture, reconcile andinteroperate metadata related to the data quality process.Configuration environment. Capabilities for creating, managingand deploying data quality rules.Operations and administration. Facilities for supporting, managingand controlling data quality processes.Workflow/data quality process support. Processes and userinterfaces for various data quality roles, such as data stewards.Service enablement. Service-oriented characteristics and supportfor service-oriented architecture (SOA) deployments.

The tools provided by vendors in this market are generally consumed bytechnology users for internal deployment in their IT infrastructure. However,off-premises solutions in the form of hosted data quality offerings and SaaSdelivery models are continuing to evolve and grow in popularity.

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Inclusion and Exclusion Criteria

For vendors to be included in the Magic Quadrant, they must meet thefollowing criteria:

They must offer stand-alone (not only embedded in, or dependent on,other products and services) packaged software tools that arepositioned, marketed and sold specifically for general-purpose dataquality applications.They must deliver functionality that addresses, at a minimum,profiling, parsing, standardization, cleansing and matching. Vendorsthat offer narrow functionality (for example, they only addresscleansing and validation or only deal with matching) are excludedbecause they do not provide complete suites of data quality tools.They must support this functionality for data in more than onelanguage and specific to more than one country.They must maintain an installed base of at least 50 productioncustomers for their data quality products.They must support the opportunity for broad-scale deployment viaserver-based runtime architectures.They must demonstrate, via customer references, that the tools areapplicable in multiple data domains (for example, product/materialsdata, financial data, customer/party data and/or other subject areas),and in enterprisewide implementations.

A vendor that does not meet the above criteria may be considered forinclusion if it is a new entrant that is demonstrably different from

established vendors, and which represents a future direction for data qualitytools.

There are many data quality tools vendors but most do not meet the abovecriteria and are, therefore, not included in the Magic Quadrant. Manyvendors provide products that deal with one very specific data qualityproblem, such as address cleansing and validation, but which cannotsupport other types of application, or lack the full breadth of functionalityexpected of today's data quality solutions. Others provide a range offunctionality, but operate only in a single country or support only narrow,departmental implementations. Others may meet all the functional,deployment and geographic requirements but are at a very early stage intheir "life span" and, therefore, have few, if any, production customers. Thefollowing vendors may be considered by Gartner clients alongside thoseappearing in the Magic Quadrant when deployment needs are aligned withtheir specific capabilities; or they are newer entrants beginning to gainvisibility in the market but which lack a significant customer base:

Acme Data, San Mateo, California, www.acmedata.com — formerlyStalworth; offers a platform for standardizing and cleansing customerdata, including international address validation.Acuate, London, U.K., www.acuate.com — provides products for thestandardization, matching and merging of various data types, as wellas data quality professional services.AddressDoctor, Maxdorf, Germany, www.addressdoctor.com —specializes in international address standardization and validation,supporting 240 countries and territories.AMB, Chicago, Illinois, http://www.ambpdm.com/ — providesprofiling, standardization and cleansing functionality for deploymentin Windows environments.Anchor Software, Plano, Texas, www.anchorcomputersoftware.com— provides a range of data quality utilities supporting commoncustomer list management operations such as file splitting,deduplication and suppression.Ataccama, Prague, Czech Republic, www.ataccama.com — the DataQuality Center product provides support for data quality analysis, datacleansing and governance of data quality business rules.BackOffice Associates, South Harwich, Massachusetts,www.boaweb.com — offers services and technology for thegovernance of master data within SAP applications.BCC Software (a division of Bowe Bell + Howell), Rochester, NewYork, www.bccsoftware.com — provides a range of data qualityutilities supporting common customer list management operations,such as address validation, change of address, deduplication andsuppression.Business Data Quality, London, U.K.,www.businessdataquality.com — offers products focused on dataprofiling (BDQ Analysis) and data quality monitoring (BDQ Monitor).Certica Solutions, Wakefield, Massachusetts,www.certicasolutions.com — provides products that focus onvalidating data against predefined data quality rules.Ciant, Richardson, Texas, www.ciant.com — provides parsing,standardization and matching functionality for customer data, insupport of sales and marketing analytics.Clavis Technology, Dublin, Ireland, www.clavistechnology.com —provides its Data Quality Governance solution, which supports thedeployment of data quality controls for preventing data entry errors,in a SaaS model.Datasegmento, Madrid, Spain, www.datasegmento.com — providesstandardization, deduplication and geocoding for database marketing.Datiris, Lakewood, Colorado, www.datiris.com — provides variousdata profiling techniques for a range of data sources.Datras, Munich, Germany, www.datras.de — focuses on the German-speaking markets, providing profiling, standardization and monitoringcapabilities.Deyde Informática, Las Matas, Madrid, Spain, www.deyde.es —specializes in name and address database optimization.DQ Global, Fareham, U.K., www.dqglobal.com — provides matching,deduplication and international address standardization and validationfunctionality.Eprentise, Orlando, Florida, www.eprentise.com — offers arule-based data quality engine for standardization, merging anddeduplication.FinScore, Renens, Switzerland, www.finscore.com — offers

technology for measuring data quality and presenting metrics in adashboard form.helpIT Systems, Surrey, U.K., www.helpit.com — provides dataquality tools oriented toward customer matching, deduplication andsuppression operations.Infogix, Naperville, Illinois, www.infogix.com — providescontrols-based technology for auditing and validating the integrity ofdata within and across systems.Infoshare, Kingston upon Thames, U.K., www.infoshare-is.com —provides data quality solutions for local and central government.Infosolve Technologies, South Brunswick, New Jersey,www.infosolvetech.com — provides open-source tools (with requiredservice contract) that support profiling, standardization, matching anddeduplication operations.InQuera, Migdal Tefen, Israel, www.inquera.com — specializes intechnology for standardization, matching and deduplication, with aspecific focus on product data.Intelligent Search Technology, White Plains, New York,www.intelligentsearch.com — develops products for profiling,matching, deduplication and U.S. address correction.Ixsight, Mumbai, India, www.ixsight.com — offers services for dataquality audits, along with products for standardization anddeduplication.Melissa Data, Rancho Santa Margarita, California,www.melissadata.com — supports standardization of names,addresses and phone numbers, and validation of addresses and phonenumbers (both via on-premises software and hosted Web services).Omikron, Pforzheim, Germany, global.omikron.net — providesproducts for standardization and deduplication of customer name andaddress data.QAS (a subsidiary of Experian), London, U.K., www.qas.com — offersglobal name and address standardization, validation andmatching/deduplication functionality.Runner Technologies, Boca Raton, Florida,www.runnertechnologies.com — provides a development componentfor verifying and standardizing addresses for Oracle databaseapplications.Sigma Data Services, Alcorcón, Madrid, Spain, www.sigma-data.com — provides data profiling, normalization and deduplicationof names, addresses and phone numbers.Silver Creek Systems, Westminster, Colorado,www.silvercreeksystems.com — provides parsing, standardization andmatching functionality, with a focus on product data applications.Spad, Paris, France, eng.spadsoft.com — offers a suite of data qualityproducts for data profiling, monitoring and standardization.SQL Power, Toronto, Canada, www.sqlpower.ca — providesopen-source tools supporting standardization, address validation anddeduplication.SRC, Orange, California, www.extendthereach.com — provides datacleansing in the context of BI applications with a geographicorientation.Talend, Suresnes, France, www.talend.com — provides open-sourceproducts for data profiling, cleansing and enrichment.TIQ Solutions, Leipzig, Germany, www.tiq-solutions.de — providesdata profiling and data quality dashboards, with a focus on thebanking, insurance and distribution verticals.Utopia, Mundelein, Illinois, www.utopiainc.com — offers services andtechnology for data quality analysis and data standardization, with afocus on product master data.Veda Advantage, Sydney, Australia, www.vedaadvantage.com —provides software to cleanse and update customer addresses, addphone numbers, merge databases into a single customer view andappend segmentation data.WinPure, Reading, U.K., www.winpure.com — offers low-cost datacleansing, matching and data deduplication software on the Windowsplatform.Zoomix (a subsidiary of Microsoft), Jerusalem, Israel,www.zoomix.com — delivers technology for adaptive matching andstandardization, with a focus on product data.

Gartner will continue to monitor the status of these vendors for possibleinclusion in future updates of the Magic Quadrant for Data Quality Tools.

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Vendors Added

No new vendors have been added to the Magic Quadrant since the previousversion.

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Vendors Dropped

No vendors have been dropped from the Magic Quadrant since the previousversion.

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Evaluation Criteria

Ability to Execute

Gartner analysts evaluate technology providers on the quality and efficacy ofthe processes, systems, methods or procedures that enable IT providers'performance to be competitive, efficient and effective, and to positivelyaffect revenue, retention and reputation. Ultimately, technology providersare judged on their ability to capitalize on their vision, and their success indoing so.

We evaluate vendors' ability to execute in the data quality tools market byusing the following criteria:

Product/Service. How well the vendor supports the range of dataquality functionality required by the market, the manner (architecture)in which this functionality is delivered, and the overall usability of thetools. Product capabilities are critical to the success of data qualitytool deployments and, therefore, receive a high weighting.Overall Viability. The magnitude of the vendor's financial resourcesand the strength of its people and organizational structure. In thisiteration of the Magic Quadrant we have increased the weighting ofthis criterion to reflect buyers' increased concern over the riskassociated with vendors as a result of current economic conditions.Sales Execution/Pricing. The effectiveness of the vendor's pricingmodel and the effectiveness of its direct and indirect sales channels.Market Responsiveness and Track Record. The degree to whichthe vendor has demonstrated the ability to respond successfully tomarket demand for data quality capabilities over an extended period.Marketing Execution. The overall effectiveness of the vendor'smarketing efforts, and the degree of "mind share," market share andaccount penetration the vendor has achieved as a result.Customer Experience. The quality of the vendor's general customerservice, implementation service and technical support, and customers'perceptions of overall value relative to pricing model and price points.In this iteration of the Magic Quadrant we have increased theweighting of this criterion to reflect the substantially greater scrutinythat buyers are placing on these considerations as a result ofeconomic conditions and budgetary pressures.

Table 1 gives our weightings for the Ability to Execute evaluation criteria.

Table 1. Ability to Execute Evaluation Criteria

Evaluation Criteria Weighting

Product/Service high

Overall Viability (Business Unit, Financial, Strategy, Organization) high

Sales Execution/Pricing standard

Market Responsiveness and Track Record standard

Marketing Execution standard

Customer Experience high

Operations no rating

Source: Gartner (June 2009)

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Completeness of Vision

Gartner analysts evaluate technology providers on their ability toconvincingly articulate logical statements about current and future marketdirection, innovation, customer needs and competitive forces, as well ashow they map to the Gartner position. Ultimately, technology providers areassessed on their understanding of the ways that market forces can beexploited to create opportunities.

We assess vendors' completeness of vision for the data quality tools marketby using the following criteria:

Market Understanding. The degree to which the vendor leads themarket in new directions (technology, product, services or otherwise),and its ability to adapt to significant market changes and disruptions.Given the dynamic nature of this market, this item receives a highweighting.Marketing Strategy. The degree to which the vendor's marketingapproach aligns with and/or exploits emerging trends and the overalldirection of the market.Sales Strategy. The alignment of the vendor's sales model with theway that customers' preferred buying approaches will evolve overtime.Offering (Product) Strategy. The degree to which the vendor'sproduct road map reflects demand trends in the market and fillscurrent gaps or weaknesses. We also consider the strength of thevendor's strategy regarding different types of delivery models, such asSaaS.Business Model. The overall approach the vendor takes to executeits strategy for the data quality market. With a reasonably high degreeof similarity across the vendors in this market, this item receives alow weighting.Vertical/Industry Strategy. The level of emphasis the vendorplaces on vertical solutions, and the vendor's depth of verticalexpertise. Given the broad cross-industry nature of the data qualitydiscipline, vertical strategies are less critical, so this item receives alow weighting.Innovation. The degree to which the vendor has demonstrated awillingness to make new investments to support its strategy andenhance its product capabilities, the level of investment in R&Ddirected toward development of the tools, and the extent to which thevendor demonstrates creative energy. In this iteration of the MagicQuadrant we have slightly decreased the weighting of this criterion, toreflect the current and near-term market demand for proven,foundational data quality capabilities with slightly less emphasis onleading-edge functionality at this point in time.Geographic Strategy. The global presence of the vendor and themanner in which it is achieved (for example, direct local presence,resellers and distributors), in light of the desire of multinationalenterprises to exploit common tools worldwide.

Table 2 gives our weightings for the Completeness of Vision evaluationcriteria.

Table 2. Completeness of VisionEvaluation Criteria

Evaluation Criteria Weighting

Market Understanding high

Marketing Strategy standard

Sales Strategy standard

Offering (Product) Strategy high

Business Model low

Vertical/Industry Strategy low

Innovation standard

Geographic Strategy standard

Source: Gartner (June 2009)

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Leaders

Leaders in the market demonstrate strength across a complete range of dataquality functionality, including profiling, parsing, standardization, matching,validation and enrichment. They exhibit a clear understanding and vision ofwhere the market is headed, including recognition of non-customer dataquality issues and the delivery of enterprise-level data qualityimplementations. Leaders have an established market presence, significantsize and a multinational presence (directly or as a result of a parentcompany).

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Challengers

Challengers in the market provide strong product capabilities but may nothave the same breadth of offering as Leaders. For example, they may lackseveral of the functional capabilities of a complete data quality solution.Challengers have an established presence, credibility and viability, but maydemonstrate strength only in a specific domain (for example, only customername and address cleansing), and/or may not demonstrate a significantdegree of thought leadership and innovation.

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Visionaries

Visionaries in the market demonstrate a strong understanding of current andfuture market trends and directions, such as the importance of ongoingmonitoring of data quality, engagement of business subject matter expertsand delivery of data quality services. They exhibit capabilities aligned withthese trends, but may lack the market presence, brand recognition,customer base and resources of larger vendors.

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Niche Players

Niche Players often have limited breadth of functional capabilities and maylack strength in rapidly evolving functional areas such as data profiling andinternational support. In addition, they may focus solely on a specificmarket segment (such as midsize businesses), limited geographic areas or asingle domain (such as customer data), rather than positioning themselvestoward broader use. Niche Players may have good functional breadth butmay have an early-stage presence in the market, with a small customer base

and limited resources. Niche Players that specialize in a particulargeographic area or data domain may have very strong offerings for theirchosen focus area and deliver substantial value for their customers in thatsegment.

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Vendor Strengths and Cautions

Datactics

Belfast, U.K., www.datactics.com

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Strengths

Datactics is a small data quality vendor headquartered in Belfast,Northern Ireland, and operates primarily in Europe. However, thevendor has recently opened a sales office in the U.S. and continues tomaintain a number of value-added resellers (VARs) in the Americasand Asia. Its software is used in a range of subject areas, beyond thetypical name/address validation scenarios. Many references report useof the software beyond the cleansing of customer data, and cite thevendor's parsing and matching capabilities as particularly strong.The company's flagship product, DataTrawler, is fully 64-bit andUnicode-enabled, supports most European languages, runs on manyplatforms and supplies broad capabilities in profiling,matching/merging, cleansing and monitoring. Data quality scorecardscan be constructed to monitor quality-related metrics. Most ofDatactics' reference customers are small and midsize businesses, witha focus on the manufacturing sector, as well as government agencies.Reference customers use DataTrawler mostly in MDM, systemmigration, and embedded into business applications.Datactics has partnerships with consultancies and system integrators(SIs) outside its U.K. base that have used the DataTrawler product insome strategic data quality programs. The vendor's own professionalservices and support function has received accolades from thesurveyed reference customers.

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Cautions

Datactics has stabilized its management, with the recruitment of anew CEO, and has successfully gone through an investment round,but the additional funds of approximately £1.8 million will not beenough to allow it to leapfrog over more financially stablecompetitors. The added sales force will need to become productivequickly for Datactics to gain momentum in its new territories. Withonly six sales employees, limited marketing budgets and relativelylow-profile partnerships, Datactics is "flying underneath the radar" formost organizations looking for a provider of data quality tools.While some customers have expressed satisfaction with Datactic'spricing and received value, an equal number were rather negativeabout the licensing and the business value received from theimplementation, particularly with regards to multiple add-on fees.Although Datactics has signed up VARs in markets such as Brazil,Hong Kong and Turkey, customers from those regions are coming inat a slow rate, and all major sales or partnering opportunities remainmostly in English-speaking countries. Datactics must build a strongerindependent software vendor (ISV) partner network to establish itselfin new markets and attract new customers.

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DataFlux

Cary, North Carolina, U.S., www.dataflux.com

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Strengths

DataFlux continues to drive broad data quality initiatives, from BI anddata warehousing to MDM and migration. With its 1,200 customers,DataFlux has become the enterprisewide data quality standard inmany large accounts. The company has one of the highest ratios ofreinvesting revenue in R&D and enjoys a maintenance renewal rate ofover 95%.The vendor continues to build out "accelerators," for example,Customer Data Analysis or Materials Data Classification, and ispraised by its customer references for the usability of its tools(particularly for non-technical staff), their easy installation and theintegration of the toolset. Technical support and professional serviceswere ranked among the highest in the customer survey.DataFlux's capabilities include profiling, matching, cleansing,monitoring and metadata management in a single platform. Throughits recently announced Project Unity, DataFlux will expand its scopeby combining Project Unity with the DataFlux MDM offering and thedata integration tools it takes over from its parent company SAS.

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Cautions

While Project Unity is the right move to follow the market trends ofintegrating data quality with data integration and MDM, there are nomarket-changing results to report. It will take the vendor about 18 to24 months to deliver a new integrated product. DataFlux will need toexpand its marketing scope to gain recognition beyond the area ofdata quality, and to compete with much larger infrastructureopponents, such as IBM, SAP or Informatica.Customers report only average satisfaction with the value ofDataFlux's software relative to its price, and some customers continueto struggle with the overall high price of the software, compared withlower-cost solutions.Although DataFlux provides broad data quality capabilities andexamples of multi-domain use are common, most recent customerreferences use name and address profiling, batch-oriented cleansingand matching, while some customers that use the tool in anon-customer domain (product data, for example) report limitedusefulness. In addition, while the software is enabled for use in aninternational environment, reference customers seem to focus onsingle-country deployments, with the majority being English-languagecountries.

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DataLever

Boulder, Colorado, U.S., www.datalever.com

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Strengths

DataLever provides support for the core requirements of data quality,providing integrated data-profiling and data-cleansing functionality ina single product. All operations can be readily deployed in both batchand real-time modes. The vendor has focused on delivering thefundamental capabilities required in virtually all data quality projects(such as parsing, standardization and cleansing), rather thanattempting to expand the scope of the data quality discipline orinnovate in new functional areas.DataLever takes a domain-agnostic view of data quality issues,enabling its technology to be applied in various data domains,

including customer and product. While most of its installed baseapplies DataLever's technology to customer data quality issues,customer references reflect a solid percentage of implementations inother areas.Customers cite overall ease of use, relatively short implementationtimes and the lower cost compared with alternative offerings as themain selling points of DataLever's products. The attractive costfootprint is well suited to the current economic and market conditions.Strong performance in scenarios with large data volumes, asdemonstrated by customer references, is helping DataLever tosucceed in competitive situations. In addition, the relatively lowcomplexity of the product means that it can be used by businesssubject matter experts, as well as IT personnel. As a result of thesecharacteristics, the vendor's mind share in the market is slowlyincreasing in North America.

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Cautions

As one of the smaller and privately held providers in the market,DataLever supports a small customer base of approximately 150, withlimited presence outside North America. DataLever's technology hastraditionally been adopted mostly by midsize businesses. However,the vendor is increasingly attracting large enterprises, but thesecustomers tend to deploy the technology within single projects or alimited set of projects, rather than enterprisewide.Although it has chosen to focus solely on its home region of NorthAmerica early in its maturity, DataLever's relative weakness ininternational support (the technology is not yet Unicode-compatible)will hinder its adoption by multinational enterprises, and its growth inother regions. Currently, the product road map calls for the vendor toaddress this gap via a partnership during 2009. An additionaltechnical weakness is the limited runtime platform support (Windowsand Linux only). To date, DataLever has focused solely on theon-premises deployment of its software. The vendor states that it willincrease its focus on SaaS delivery in 2009, although it has taken noapparent action in this direction.The vendor's lack of significant partnerships with SIs andcomplementary software vendors will limit its competitive strength —this represents a substantial challenge in the current marketconditions, where buyers perceive greater risk in smaller vendors.DataLever must begin to look beyond its own intellectual property andcapabilities to improve its ability to execute by broadening itsmarketing and delivery reach while also expanding its perceivedfunctional breadth.

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DataMentors

Wesley Chapel, Florida, U.S., www.datamentors.com

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Strengths

DataMentors specializes in customer data quality applications,providing matching, linking, standardization and cleansing operationsvia its DataFuse product, and data profiling capabilities via ValiData.Its partnership with smartFocus enables the vendor to offer campaignmanagement, analytics and mapping capabilities (branded asDataMentors' PinPoint). The vendor's roots are in database marketing,with the management team having been involved in large-scaleapplications of this type for more than 20 years.Customer references are predominantly in the financial servicesvertical, although the vendor is increasing its focus on the healthcare,hospitality and publishing industries. Customers cite accuracy ofmatching, ease of use and attractive pricing relative to some of themore prominent vendors in the market as key strengths, and thereasons for their selection of DataMentors' technology. With a new

version of DataFuse recently delivered (including parallel processingfor improved performance on SMP hardware, and a broader range ofmatching algorithms), the vendor will turn its attention to enhancingthe ValiData profiling product to improve the user experience andmake it consistent with DataFuse (this is planned for later in 2009).The longer-term product road map includes delivery of the 64-bitDataFuse 6.0 platform, with Web-based and mobile functionality.The vendor's customer base reflects a higher percentage of hosted(SaaS) implementations than is seen for any other vendor in thismarket. DataMentors estimates that more than half its customers areusing its technology in a hosted manner and that nearly all newcustomers are deploying the technology in a SaaS model. This isreflected in the vendor's customer references.

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Cautions

With a small installed base (approximately 100 customers, all in NorthAmerica) and limited resources for marketing, DataMentors will bechallenged to gain mind share in a market increasingly populated bymuch larger providers. In addition, while the vendor's attractive costmodel and ease of use are well suited to market demand, as one ofthe smallest competitors in this market it will face challenges as thecurrent economic conditions increase buyers' desire for largeproviders with extensive financial resources.DataMentors' substantial focus on customer data quality issues willplace it at a competitive disadvantage when prospects have broaderdata quality requirements, including quality issues in non-customerdata domains. However, the vendor's customer references do reflectexamples of the use of the technology in product data quality andfinancial data quality applications.From a product functionality perspective, DataMentors hasweaknesses in runtime platform support (Windows is the onlydeployment option, although DataFuse can interact with applicationsand data sources on other platforms) and international capabilities,because of a lack of Unicode support. Customer references reflectvery limited usage in real-time scenarios and few examples of multi-project or enterprisewide deployment.

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Datanomic

Cambridge, U.K., www.datanomic.com

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Strengths

Datanomic continues to establish itself in the European data qualitytools market and has enjoyed its first year of profitability. The vendoris approaching 150 customers, most of which are in the U.K., withsome in mainland Europe and about 10% in North America and Asia.As a relatively new player, Datanomic has been able to build itsdn:Director platform on modern technology, without any major legacybaggage.The new Web services capability enables dn:Director users to rapidlydeploy data quality components, such as matching or cleansing, intoSOA environments. Datanomic has also released new extension packs,for customer data and sanctions and politically exposed persons(PEPs), enabling customers to speed up the time to production.Datanomic has also enhanced its real-time capabilities, added newdata quality processors into the product and continued to improve thepresentation functionality with tailorable user interfaces suited todifferent user types. Finally, ease of implementation and ease of useare cited by customer references as dn:Director's particular strengths.About three quarters of Datanomic's customers come from thefinancial and telecommunications industries and the public sector, andthe vendor has a strong focus on those areas. Datanomic products aredomain-agnostic and not specifically targeted at customer data,

although hardly any surveyed customer references reported a focus onnon-customer data. At the same time, references indicate a very highsatisfaction with the professional services and support fromDatanomic.

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Cautions

While dn:Director is built on an SOA, and its database connectivity isexpanding to cover access to Oracle, Microsoft, Sybase and now alsoDB2, a native adapter for Teradata is not available. Hardly anyreferences report using the product outside customer/party datadomains and address cleansing.Although dn:Director is built in a services fashion, Datanomic has notvisibly started to offer its data quality solution in a SaaS model.Almost all customer references indicate that they installedDatanomic's products on-premises.Datanomic has been unable to capitalize on the international reach ofits SI partners, some of which are very large, leaving it with virtuallyno visibility outside its home market in the U.K. In addition,Datanomic's relatively small size and market presence remainsignificant challenges in the face of economic conditions in its homemarket and increasing competitive pressure from much largerapplication and infrastructure providers.

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Human Inference

Arnhem, The Netherlands, www.humaninference.com

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Strengths

Human Inference, based in Arnhem, the Netherlands, provides dataquality solutions to customers almost exclusively in the Europeanbanking, insurance and services industries. As one of the largestindependent providers of data quality software in Europe, HumanInference enjoys good brand recognition, particularly in Benelux andGermany, where the vendor runs successful marketing events.The components of the HIquality product set include technology forinspection and profiling, name and address cleansing, matching,merging and enrichment. One of Human Inference's keydifferentiators, described as a major strength by reference customers,is that it maintains reference datasets, which are available for selectcountries and which serve as knowledge bases for names, addresses,cultures and other specific meanings from a variety of contexts. Inaddition, Human Inference has started to focus on provisioning dataquality through SaaS, which makes HIquality more attractive as anembedded component in business processes.A large portion of Human Inference's customer base has gone beyondbatch processing and embarked on real-time matching and cleansing,while fewer reference customers had implemented Human Inference'sdata quality products in a BI context. The vendor's products aredescribed as particularly strong in an MDM environment and whenembedded into operational applications.

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Cautions

Most reference customers had not upgraded to the latest availablerelease of HIquality. Some customers reported a reluctance to migrateto the latest version of the product because of high complexity andcost during the migration process, even describing the newer versionsas "black box." To ease migration, Human Inference has invested inan update pack, released earlier in 2009. A relatively high ratio ofcustomers also indicated issues with access to skilled service

personnel and software pricing, while customer feedback on serviceand support was only average and significantly lower than for thevendor's peer group.Human Inference's partner channel strategy is still at an early stage.The vendor's OEM and reseller partnerships with SIs and ISVs areonly slowly getting traction, as the vendor relies heavily on its directsales channel. While Human Inference still has a stronghold in its coregeography, it will experience greater competitive pressure from thelarge infrastructure vendors.Human Inference recently underwent some management changes,including the recruitment of a new CEO, generating some uncertaintyabout the vendor's potential strategy changes.

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IBM

Armonk, New York, U.S., www.ibm.com

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Strengths

IBM has successfully embedded its data quality products portfolio intoits broader Information On Demand message. By promoting IBM'splatform vision, ubiquitous data quality functionality becomes a keycomponent of the information management portfolio. Backed by oneof the world's best-known brands and strong sales, consulting,service and support functions, IBM approaches the data quality marketfrom many angles.Information Analyzer (discovery, profiling and analysis) andQualityStage (parsing, standardization and sophisticated matching)continue to be positioned as enterprisewide data quality standards,and are being used in several projects in customer organizations.IBM's customers have started to use its data quality products inmultiple data domains, beyond customer data.Reference customers report high satisfaction with the scalability andperformance of the solution. Also, customers praised the integratednature of the solution across the various modules, including profiling,matching, cleansing and metadata management.

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Cautions

IBM's Information On Demand message and the newer "informationagenda" theme distract from the focus on data quality. While dataquality is part of the overall message and IBM initiated a data qualitycommunity with its Data Governance Council, mind share in themarket grows relatively slowly. In particular, for organizations thatwant to focus on data quality as a separate initiative to solve aspecific problem, the grand Information On Demand theme is likely tobe seen as overkill. Still, in large enterprise deals, particularly thoseled by the IBM consulting and services organization, IBM's dataquality products are always a contender.The high price points of IBM's products relative to some othercompetitors represent a challenge for IBM. Customer referencesreported only average satisfaction with the pricing model and relativevalue of the products. Some customers expressed dissatisfaction withthe pricing of individual modules, and with the lack of availability ofqualified resources for implementation and support.Although smaller competitors have embarked on a SaaS model fordata quality, IBM has not addressed this new market segment, despiteits extensive hosting capabilities. Reference customers are using IBM'sdata quality products in an on-premises fashion exclusively.

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Informatica

Redwood City, California, U.S., www.informatica.com

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Strengths

Informatica has established itself as a prime provider of data qualitysolutions in the market with impressive growth figures, particularly inEurope, the Middle East and Africa (EMEA) and Asia/Pacific. Thevendor added a significant number of large data quality deals to itsinstalled base, many of which are net new customers. In addition,cross-selling of data quality tools to the existing PowerCenterinstalled base works well for Informatica. The installed base of itscore data quality products (Informatica Data Quality and InformaticaData Explorer) is estimated at approximately 800 customers, and alarge proportion of customers consider Informatica's tools their dataquality standard.Informatica's data quality tools portfolio includes strong data profilingfunctionality (Data Explorer) and domain-agnostic parsing,standardization and matching capabilities (Data Quality). WhileInformatica does not offer an MDM solution itself, the company'sacquisition of Identity Systems enables Informatica to play asignificant role in entity resolution and supporting customers' MDMinitiatives.Customer references reported high satisfaction with the performanceand scalability of the data quality tools, in addition to the professionalservices provided. A large proportion of Informatica's customers havealso expanded the range of data quality domains in which they areusing the tools, beyond customer data, into product data, financialdata and other types of data. The ease of use of the products andpositive service and support experiences were also cited by customerreferences as significant strengths. Finally, Informatica benefits fromthe tight integration of data quality components with its flagshipproduct, PowerCenter.

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Cautions

While the bread-and-butter capabilities of the Informatica data qualityplatform, such as parsing, matching and cleansing, are usedextensively and with high satisfaction within the reference customerbase, enrichment, geocoding, internationalization and data qualityworkflow functionalities received low ratings, and reference surveyresults show that less than 10% of customers are using thesecapabilities.Informatica continues to be challenged in its indirect sales channel fordata quality products, because longtime infrastructure andapplications partners have either acquired data quality technologythemselves or are looking for other vendors for complementary dataquality technology, as they now compete against Informatica in thedata integration tools market.Informatica is increasingly competing against much largerinfrastructure vendors with broader product sets, including MDM, BIand other capabilities. These vendors represent a significantcompetitive threat, since they are incumbents for many of thecustomers and prospects Informatica is targeting with its data qualitytools message. Still, most customer references use Informatica dataquality tools in a BI, migration or information governance context,and a growing number of customers also reported usage incombination with an MDM initiative.

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Innovative Systems

Pittsburgh, Pennsylvania, U.S., www.innovativesystems.com

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Strengths

Innovative Systems has competed in this market longer than mostother vendors, with a history spanning nearly 35 years. Innovative'si/Lytics platform provides proven capabilities based on its deepexperience in customer data matching and cleansing applications.i/Lytics provides strong support for both mainframe and distributedplatforms, and enables data quality functionality to be exposed viaservice interfaces. Customer references reflect usage of thetechnology in a real-time deployment mode embedded withinindividual operational applications, but with less usage in otherscenarios such as BI architectures and MDM applications.Complementing its financial services experience, Innovative continuesto focus on its FinScan compliance watchlist-screening offerings, anarea that is showing continued strong demand. During 2008, thecompany experienced substantial growth in the market adoption ofthis offering. In addition, it is placing more emphasis on deliveringi/Lytics functionality in a SaaS model, in line with a growing trendtoward hosted and hybrid (a combination of on-premises and hosted)deployments in this market. Innovative's customer references includeexamples of both delivery models.Innovative's customer base (approximately 250 customers, most ofwhich are large enterprises) reflects the vendor's strong experience inthe banking and insurance industries — the financial services verticalscomprise nearly 90% of the vendor's customers. While slightly morethan one-half of its revenue is derived from North America, Innovativealso supports customers in Europe and is experiencing growth in LatinAmerica (a region in which it has significant experience). Customerreferences report a very positive service and support experience, andsuccess with multi-project deployments.

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Cautions

With a strong emphasis on customer data quality issues, Innovativewill be challenged to win new business or expand its presence inexisting accounts when multi-domain data quality capabilities arerequired. Customer references reflect virtually no use of thetechnology in other data domains, such as product/materials data orfinancial data. Since market demand for multi-domain support isalready significant and growing, Innovative will need to rapidlyaddress this weakness to improve its market presence beyond nichespecialist status.Innovative's product road map includes most technical enhancementsto existing functionality. The vendor's data profiling and qualityvisualization capabilities continue to see limited market adoption, witha small fraction of customer references having adopted thisfunctionality. Some of those customers that are using the profilingfunctionality cite this as an area of weakness. In addition, whileInnovative's technology can support multilingual data, the lack of fullUnicode capabilities limits Innovative's ability to compete on a globalbasis.Given its long history in the market, Innovative's relatively smallinstalled base indicates limited growth in recent years, although 2008results showed a net increase in the customer base of nearly 20%. Acustomer base overwhelmingly weighted toward financial servicesrepresents a significant challenge given the current economicconditions and turmoil in that industry, as well as the increasingdemand from buyers in all industries for vendors to providereferences of similar customers.

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Netrics

Princeton, New Jersey, U.S., www.netrics.com

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Strengths

Netrics provides a range of capabilities with a specific focus onmatching. The vendor uses a machine learning approach toimplementing matching and standardization, based on the customer"teaching" the technology about the characteristics of matches byworking through a sample set of data. Netrics is actively targetinggovernment organizations and the healthcare industry — twosignificant opportunities during the challenging economic conditions,and areas where matching and relationship identification capabilitiesare in demand.Netrics' technology is essentially an embeddable data quality andmatching engine, enabling the deployment of data-quality-relatedservices inside any type of application. This is a significantdifferentiation from most other vendors in the market, and enablesNetrics to focus primarily on an indirect channel strategy with OEMand SI partners. The most recent release of the technology added aWeb services application programming interface (API) for applicationsto communicate with the engine.Customer references claim better accuracy in highly complex matchingproblems compared with more traditional matching approaches, witha shorter time to implementation because comparatively less"programming" is needed. References also reflect the lack of domainbias in Netrics' technology — customers are working with varioustypes of data, including customer, product and location data in MDMinitiatives. To further its positioning toward MDM scenarios, Netricshas established a partnership with MDM solutions provider DataFoundations. In addition, references report a very positive experiencewith the ease of use (referring to the ease with which developers canembed the technology programmatically into their applications),technical support and performance of the technology.

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Cautions

Netrics' strong emphasis on matching comes at the expense of otherdata quality operations, such as profiling and address validation, inwhich it has limited capabilities compared with most other vendors inthis market. The lack of a user interface, other than a Web-basedconsole for administration of engine operations, means that thevendor does not provide prebuilt functionality for the visualization ofprofiling results, matching results or runtime statistics — capabilitiesthat are increasingly important as organizations focus more stronglyon ongoing information governance and want to expose data qualityfunctionality to non-technical roles.Netrics' product road map of confirmed enhancements includes mostlytechnical improvements, such as additional functionality that willincrease the matching flexibility of the engine. A significantdevelopment will be the delivery of Unicode support during 2Q09.However, the road map is otherwise limited in terms of enhancementsthat would fill critical gaps relative to larger competitors, such asrobust data profiling functionality, or support for richer parsing,standardization and validation rules (in particular for the customerdata domain, a mainstay of demand in the data quality tools market).With a small installed base (approaching 200 customers) and limitedresources for marketing, Netrics will be challenged to gain mind sharein a market increasingly populated by much larger providers and inthe face of economic conditions. Customer references comprise a mixof midsize and large organizations, although some of the applicationsin which Netrics' tools are embedded (including applications deliveredby some of its OEM partners) support very large numbers of users.

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Pitney Bowes Business Insight

Stamford, Connecticut, U.S., www.pbbusinessinsight.com

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Strengths

Pitney Bowes Business Insight (PBBI), which competes in the dataquality tools market as a result of the acquisition of Group 1 Softwareby Pitney Bowes, continues to focus on its traditional positioning of"customer data quality," with extensions to related data domains ofasset and location. The vendor specializes in global name and addressstandardization and validation, matching-related capabilities(including linking and deduplication) and geocoding. Thisfunctionality is supported on a range of platforms, including themainframe. Although the vendor's underlying technology can beconsidered domain-agnostic, customer data quality applications areits primary focus, as is clear from the Customer Data Quality Platform(CDQP) product naming.PBBI has oriented its messaging around the concept of customer,asset and location intelligence. Location capabilities, including richgeocoding and mapping functionality, are a key extension to CDQP,enabling the vendor to respond to the trend of growing demand formanagement of location-specific data. Capabilities gained via the2007 acquisition of MapInfo form the basis of these extensions to thecore data quality offerings. Additional developments in the productroad map during the next 12 months include mainly customer-data-specific functionality (such as expanded Coding AccuracySupport System [CASS] support and e-mail validation),location/mapping functionality (routing algorithms and geocodingimprovements), and technical and operational enhancements (64-bitsupport, various platform and API extensions, and versioning).PBBI retains a large installed base (more than 2,400 customers),making it one of the market-share leaders for data quality tools. Thevendor's large scale and global footprint give it greater stability incomparison with many competitors of much smaller stature. Revenuesreflect an installed base that is very North-American-centric, withlarge enterprises making up most of its customers. Deploymentuse-cases reflected by customer references include BI architectures,MDM solutions, and real-time use within operational applications.

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Cautions

PBBI's strong focus on customer data places it at a competitivedisadvantage compared with providers with multidomain-capabletools. Customer references report no use of the technology outside ofthe customer/party and location data domains, which is consistentwith the vendor's product positioning. While the vendor's recentmarketing partnership has yet to show positive impact, the productroad map for 2009 calls for delivery of a technology adapter forintegration with Silver Creek Systems, which will enable PBBI to morereadily approach customers with multi-domain needs.The vendor continues to see extremely limited adoption and use of itsprofiling, visualization and monitoring functionality. Customerreferences reflect no examples of these capabilities in use. Lack ofproof points in this regard represents a substantial weakness for PBBI,since these are among the most rapidly growing areas of demand inthe market.While PBBI offers a range of pricing models and options,mainframe-based customers (which represent the core of its customerbase) continue to report challenges in negotiating the cost ofupgrades and ongoing support/maintenance, as well as workingthrough renegotiations of enterprise licenses, including mainframeproducts. Although customer references generally cite a very positivetechnical support and professional services experience, the cost modelassociated with the technology is perceived as adequate butsometimes a challenge.

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SAP BusinessObjects

Walldorf, Germany, www.sap.com

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Strengths

SAP BusinessObjects has a substantial BI platform market presenceand a large base of data quality tools customers (most of which are inNorth America and in German-speaking countries and were obtainedthrough Business Objects' earlier acquisitions of Firstlogic and FuzzyInformatik). This creates significant cross-sell opportunities for thevendor to increase its data quality tools business. As a part of SAP,the vendor's growth prospects are further expanded via access to theglobal SAP applications customer base, where data quality challengesare prevalent. In particular, SAP BusinessObjects' data quality toolscomplement SAP's MDM solution, which has been lacking rich dataquality functionality. SAP has delivered initial integration between itsdata quality tools and its MDM offering, with deeper integrationplanned in the product road map.Business Objects provides a good breadth of functional data qualitycapabilities, including data profiling (via Data Insight XI) andcommon data-cleansing operations (via Data Quality XI). The coredata quality functionality in Data Quality XI enables the delivery ofdata quality services in an SOA context, and is used in the DataServices product (which combines data integration and data qualityfunctionality). Consistent with increasing market demand for tightlyintegrated data integration and data quality functionality, DataServices is seeing increased adoption by SAP BusinessObjectscustomers. The vendor's vision includes a focus on data governanceand support for business-oriented roles.SAP BusinessObjects' strength in this market remains very much inapplications of customer/party data quality, specifically inmatching/linking, deduplication and name and addressstandardization and validation. The technology is proven forapplications of this type and such implementations represent the vastmajority of the installed base. During the past several quarters, thevendor has delivered a number of data quality-related enhancements,most of which were focused specifically on functionality forcustomer/party data (such as addressing engines and geocodingfunctionality for additional countries and languages, as well asintegration with SAP and Siebel CRM applications).

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Cautions

Customer deployments continue to reflect very few cases where thetechnology is being applied in data domains beyond customer data(and similar "party"-oriented subject areas such as suppliers oremployees). While this is because of historical optimization of thetechnology for customer data, the Universal Data Cleanse (UDC)product enables broader use. However, UDC is still new with a limitednumber of production implementations.Data profiling remains an area of relative weakness for SAPBusinessObjects. The Data Insight product continues to show slowmarket adoption and customer references report limited use andsignificantly lower levels of satisfaction with the functionality,compared with the profiling offerings of many competitive vendors.SAP BusinessObjects' product road map calls for delivery of "next-generation" capabilities, but not until around 2010.Compared with one year ago, customer references indicate a declinein the quality of technical support, professional services and theirsatisfaction with the price-value ratio of SAP BusinessObjects' dataquality tools. While there could be various reasons for this decline,the turnover of personnel following the acquisition of BusinessObjects, the substantially larger size and complexity of the SAPorganization, and the current economic conditions (where high-pricedproducts create challenges for customers) are likely to be contributingfactors.

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Trillium Software

Billerica, Massachusetts, U.S., www.trilliumsoftware.com

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Strengths

Trillium Software, a division of marketing services provider Harte-Hanks, provides a broad suite of data quality tools, including dataprofiling (TS Discovery), core data quality components (TS Quality)and a data quality dashboard offering (TS Insight). Its dataenrichment capabilities are focused on customer data (addresses,geocoding and watchlist compliance). Trillium is attempting to expandits positioning and capabilities beyond core data quality functionstoward what it calls "Data Intelligence and Governance (DIG),"offering a combination of technology and professional services aimedat data governance initiatives in the financial services industry.Trillium continues to enjoy strong brand recognition and customerretention, and remains a market-share leader with a large installedbase of over 800 customers. The vendor has a strong North Americanpresence, but has also increased the revenue contributions fromEMEA, Asia/Pacific and Latin America to nearly 40%. The customerbase reflects a diversity of use cases, including those within BIactivities, MDM solutions and in support of data governanceprograms. The vast majority of customer references are using thetechnology in the customer/party data domain. Customer referencescite the profiling and visualization functionality, base datamanipulation functionality (parsing and standardization), andmatching functionality as strengths of Trillium's technology. Inaddition, customers generally report a high level of satisfaction withthe performance and scalability of Trillium's tools, and a very positiveservice and support experience.Trillium has a high-profile relationship with Oracle that represents itsmost significant partner channel. Trillium's data quality functionalityis sold as an add-on option for Oracle Data Integrator, and isintegrated with the Oracle E-Business applications. Trillium's resellerpartnership with Teradata and a new technology alliance withSyncsort further expand the size and quality of Trillium's indirectsales and marketing footprint.

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Cautions

Trillium's functionality, marketing and product road map havehistorically been largely geared toward data quality issues incustomer/party data. Its ability to adapt to non-customer/party data,including the functionality, experience and credibility in that domain,remains a weakness that Trillium must address to remain competitiveas market demand becomes increasingly multi-domain in nature.Despite this weakness, an increasing number of existing Trilliumcustomers are applying the technology against product/material andother kinds of data.As Trillium begins to target a non-IT audience and business roles withits vision for data governance, it will need to continue to improve theusability of the technology. According to customer references, theease of use of the tools is adequate, but there is a requirement forspecialist technical skills. This represents an important area ofimprovement for Trillium, as the ownership and maintenance of dataquality rules will increasingly be a component of business-user rolesrather than IT roles.While many of its competitors offer data quality tools as part of abroader portfolio of data management technology, Trillium hasretained its strategy of being a data quality specialist. While marketdemand for stand-alone data quality tools remains healthy, demandcontinues to shift toward a desire for tightly integrated dataintegration, MDM and data quality capabilities. Trillium's dataintegration tools partners will help it to address this trend (althoughthe partnership with Oracle is relatively new), but the vendor willexperience increasing pressure from the other market leaders andvarious other competitors that offer broader functionality.

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Uniserv

Pforzheim, Germany, www.uniserv.com

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Strengths

Uniserv, which is based in Pforzheim, Germany, is the largestpure-play provider of data quality solutions in Europe, with almost 40years of history, more than any other vendor in this roundup. Thevendor focuses almost exclusively on customer data, name andaddress verification and geocoding. About 75% of Uniserv's revenueand customers are in Germany, France and the U.K., but the vendorhas also sold in other European countries and the U.S.Uniserv has found solid traction beyond batch-oriented data qualitysolutions and a number of customer references report that they areusing the vendors' SaaS delivery model. Almost all references reportusing the vendor's product equally in batch and real-time processingenvironments. Uniserv has expanded its product portfolio and througha reseller agreement is now also providing comprehensive dataquality monitoring and data profiling with its DQ Explorer product.The Uniserv product set is fully Unicode-enabled and is one of veryfew that operate on a wide variety of system platforms, from all majorWindows and Unix/Linux versions to IBM mainframes under z/OS andVirtual Storage Extended (z/VSE), as well as IBM System i andSiemens BS2000.

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Cautions

As many organizations start to view data quality as a domain-agnosticissue, Uniserv's strong focus on address standardization andvalidation will put it at a competitive disadvantage compared withother providers that market themselves with a broader data qualityview concerning, for example, product data or financial data. WhileUniserv covers address validation for almost 200 countries, noreferences have reported using Uniserv's product in any data domainother than address data.Uniserv is an established brand for matching, merging, cleansing andaddress and bank data verification technologies, but it does not serveincreasingly popular areas such as data quality dashboards. Referencecustomer feedback on Uniserv's technical support, professionalservices, ease of implementation and pricing is about average, withthe occasional praise and complaint.Uniserv's strong concentration on its direct sales force, and its lack oflarge international alliances with SIs and ISVs that use Uniservtechnology as OEMs, put the vendor under increasing pressure fromthe larger infrastructure providers. In addition, both its partners SAPand Oracle have either acquired or embedded data quality technologyfrom Uniserv's competitors.

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The Magic Quadrant is copyrighted 9 June 2009 by Gartner, Inc. and is reused with permission.

The Magic Quadrant is a graphical representation of a marketplace at and for a specific time

period. It depicts Gartner's analysis of how certain vendors measure against criteria for that

marketplace, as defined by Gartner. Gartner does not endorse any vendor, product or service

depicted in the Magic Quadrant, and does not advise technology users to select only those vendors

placed in the "Leaders" quadrant. The Magic Quadrant is intended solely as a research tool, and is

not meant to be a specific guide to action. Gartner disclaims all warranties, express or implied,

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