Gartner believes this represents a renewed focus on either vision or execution without addressing all the requirements of data integration software. In this Magic Quadrant, Gartner evaluates the strengths and weaknesses of 16 providers that it considers most significant in the marketplace, and provides readers with a graph (the Magic Quadrant. Gartner Magic Quadrant for Enterprise Data Loss Prevention (DLP) 2020, 2019 & 2018 Where is it? It’s 2020, so where is the latest Magic Quadrant for Enterprise Data Loss Prevention (DLP)? It turns out that the last and final Magic Quadrant for Enterprise Data Loss Prevention (DLP) report was published early Feb. Security event monitoring, user activity monitoring and compliance reporting. The technology provides realtime security monitoring, historical analysis and other support for incident investigation and compliance reporting. Return to Top Magic Quadrant Figure 1.
The editors at Solutions Review highlight what’s changed since the last iteration of Gartner’s Magic Quadrant for Data Quality Solutions and provide analysis of the new report.
Analyst house Gartner, Inc. recently released the 2020 version of its Magic Quadrant for Metadata Management Solutions. Gartner defines the software category as “a core aspect of an organization’s ability to manage its data and information assets. The term “metadata” describes the various facets of an information asset that can improve its usability throughout its life cycle.” Metadata simply summarizes data, which has the ability to make finding and working with relevant information easier. Metadata can be created manually by a user, or automated by a data processing tool. Metadata commonly describes how and when and by whom a particular data set was created and what native format it resides.
Commonly used as a reference for business-centric projects, metadata is instrumental for describing, inventorying, and understanding data for multiple use cases. The most common include data governance, risk and compliance, and data analytics. Selecting the best metadata management product can be a difficult task due to the high degree of specialization among vendors in this space. Gartner adds: “The market for metadata management solutions is complex because these solutions are not all identical in scope or capability.”
The solution providers included in this Magic Quadrant offer one or more of the many traditional metadata management capabilities like metadata repositories, a business glossary, data lineage, impact analysis, rules management, semantic frameworks, or metadata ingestion and or translation. Vendors also had to demonstrate to Gartner the ability to identify, document, and maintain relationships between ingested and translated metadata to be included.
In this Magic Quadrant, Gartner evaluates the strengths and weaknesses of 17 providers that it considers most significant in the marketplace and provides readers with a graph (the Magic Quadrant) plotting the vendors based on their ability to execute and their completeness of vision. The graph is divided into four quadrants: niche players, challengers, visionaries, and leaders. At Solutions Review, we read the report, available here, and pulled out the key takeaways.
Gartner adjusts its evaluation and inclusion criteria for Magic Quadrants as software markets evolve. Solidatus has been added to the report while Global IDs was dropped.
Informatica retains its spot at the top of Gartner’s Magic Quadrant for another year, distancing itself from the next closest competitor. Informatica appears more than any other metadata management vendor in competitive situations seen by Gartner. IBM made a notable move up Gartner’s vertical axis making it next up to challenge Informatica’s dominance in this data management space. IBM is also seen in a high percentage of competitive situations by Gartner and represents an established metadata management standard for the largest of organizations.
Collibra remains a strong player in the leader column and touts a product development roadmap that aligns well with current market conditions. Customers use Collibra in an array of delivery options, and the product has a growing user community. erwin made notable gains on Gartner’s Ability to Execute axis and now retains solid footing among the major metadata management players. erwin Data Intelligence Suite is a complete offering with strong data governance capabilities, according to reference users.
Alex Solutions has grown its list of channel partners by roughly 150 percent since 2019, and customers often select its metadata management platform for ease of deployment and use. Alex Solutions also supports a broad range of use cases. Alation is also maintaining its leader status, buoyed by an explosion in interest for its data cataloging platform. Alation has also continued to extend its machine learning-based features at a rapid rate.
Oracle, SAP, Smartlogic, and ASG form a bloc in the lower left-third of the leader column and round out the major players. Oracle is best-fit for complex deployments, features connectors for metadata ingestion, and uses metadata management as a basis for core capabilities like business continuity and data movement, transformation, and governance. SAP utilizes metadata integration for multiple DBMS platforms and enables users to monitor, report, audit, and forward engineer. SAP has also initiated a new focus on metadata-driven solutions throughout its product line.
Gartner reference customers report using Smartlogic for a wide range of metadata management use cases like revenue leakage prevention, data quality and governance, and compliance. Smartlogic’s architecture is scalable, and the vendor secured more above-average scores from users than any other provider in the field. ASG Data Intelligence features what Gartner calls an “intuitive interface” with a broad range of functionality. The product is based on business use cases and offers support for 260 data sources and data lineage.
Read Gartner’s 2020 Magic Quadrant for Metadata Management Solutions.
Timothy King
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Throughout the year, IT consulting firm Gartner releases their research and findings regarding a variety of market trends, in the form of Magic Quadrants. These reports highlight the top vendors in the field for different categories, along with their strengths and cautions, providing insights to key decision makers.
Just like others Magic Quadrants, the 2020 Gartner Magic Quadrant for Data Quality Solutions has been eagerly anticipated by organizations and clients alike, shedding light on top innovators in the field and what we can anticipate in terms of new solutions in the coming year.
New changes, new name
Given the fast innovation of technologies and expansion in market demands, Gartner changed the name of this Magic Quadrant this year from “Magic Quadrant for Data Quality Tools” to “Magic Quadrant for Data Quality Solutions.”
In previous years, this Magic Quadrant addressed the tools that typically offered effective data management capabilities, but Gartner acknowledged that efficient data quality practices require much more than just tools; companies rely on complete data quality solutions that support a variety of use-cases across different disciplines and industries. With this in mind, the research firm chose to reflect these changes in the vendors involved and criteria required.
Market definition of Data Quality Solutions
Gartner defines data quality solutions as “the processes and technologies for identifying, understanding and correcting flaws in data that support effective data and analytics governance across operational business processes and decision making.”
As the market for data quality solutions continues to expand and closely integrate with offerings such as metadata management solutions, data integration tools, and master data management, data quality solutions vendors are being expected to:
- Collaborate more with users and business leaders.
- Help operations run more efficiently.
Gartner List Of Magic Quadrants
Some solutions offered by these vendors include parsing, cleansing, profiling, standardization, enrichment, matching, and monitoring.
In order to qualify for inclusion in this quadrant, vendors must:
- Deliver core data quality functions such as matching, business rule creation, parsing, profiling, cleansing, or multidata domain support.
- Provide stand-alone on-premises software solutions that are sold specifically for data quality applications.
- Support multiple data domains across different industries.
- Maintain an installed base of more than 100 production customers for their products.
- Offer large-scale deployment via cloud-based and server-based runtime architectures.
Magic Quadrant for Data Quality Solutions 2020
The Magic Quadrant for Data Quality Solutions is represented here:
(Source)
Gartner Magic Quadrant Reports
Results at-a-glance
In order to fully utilize the results of the Data Quality Solutions Magic Quadrant, it’s necessary to understand each category:
- Leaders: Innovative giants who demonstrate depth across the full range of data quality solutions.
- Challengers: Companies that have an established presence along with robust product capabilities.
- Visionaries: Innovators who demonstrate a strong understanding of current and future trends in the market.
- Niche Players: Specialists who are often hyper-focused in a limited number of geographic areas or industries.
With these category definitions in mind, below are the results comparing last year’s Magic Quadrant to this year’s final results.
| 2020 Results | 2019 Results | |
| Leaders | Informatica IBM SAP SAS Talend Precisely | Informatica IBM SAP Talend Syncsort Oracle |
| Challengers | Oracle Experian Innovative Systems | Pitney Bowes Experian |
| Visionaries | Ataccama Information Builders MIOsoft Infogix | Information Builders Ataccama MIOsoft |
| Niche Players | Redpoint Syniti Melissa Data | RedPoint Global Innovative Systems BackOffice Associates |
Dominant Leaders
Although the three main vendors remained consistent in the Leaders Quadrant from 2019 to 2020, the rest of the category saw some new additions and dropouts.
Informatica
Informatica once again commands the top spot, rightfully placed there due to their four data quality solutions and deep understanding of the market. Both its multidomain support and data profiling features are consistently ranked as best-in-class, and their superior ease-of-use contributes to their continued Leader position.
Customers do report that installing their solutions is very technical, and their prices are steep compared to competitors. These are some areas to be looking for changes in the coming years.
IBM
With IBM’s Watson Knowledge Catalog being released in June, it brought to the industry some of the most forward-thinking machine learning and AI technologies of any other similar products on the market. IBM’s deep understanding of needs and demands continues to solidify its position as a Leader, with its data quality solutions modernizing the platform and integrating data governance, data quality, and data consumption into one experience.
A few cautions to keep in mind, though, are IBM’s plans to migrate its existing InfoSphere Information Server customers to the Watson Knowledge Catalog, as well as its more difficult product installation process.
SAP
Rounding out the top three vendors in the Leader category is SAP, who actually possesses the biggest market share of any data quality solutions vendor. With its innovative cross-tool integration strategy, SAP aims to provide tighter connectivity among its data management capabilities, including:
- Metadata governance
- Data integration
- Data preparation
The company does face some general challenges, with noted needs to improve its user interface for a better overall experience, along with continuing to improve their technical support.
Vendors added and dropped
Added:
- Infogix
- Melissa Data
- Precisely (formerly Syncsort)
- Syniti (formerly BackOffice Associates)
Dropped:
- Pitney Bowes (acquired by Syncsort in December 2019)
Data Quality Solutions in 2020
Although the main Leaders in the Data Quality Solutions Magic Quadrant remained the same again this year, the promises of innovative technologies and competitive pricings make this category something to keep an eye on. With more capabilities being added as data quality solution options, the landscape will only continue to change, bringing new ideas and growth.
Additional resources
Want to view more Magic Quadrants? Explore these resources: