Gartner Magic Quadrant for Data Governance 2024: What to expect

Updated September 29th, 2024

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Gartner produces a variety of annual Magic Quadrant and Critical Capabilities reports to provide companies with objective guidance for selecting software that will meet their business needs. Using Gartner’s insights, organizations can determine how to invest in tools that solve current problems and keep them on top of emerging trends.
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One of these influential annual reports is Gartner’s Data and Analytics Governance Platforms. For years, Gartner has emphasized the impact that proper data governance can have on a company’s bottom line and, more recently, how data governance has become even more crucial as more countries implement data privacy laws.

Here’s a look at the categories Gartner evaluates when making its Magic Quadrant and Critical Capabilities ratings in general, and also what the company currently recommends when it comes to data governance.

Table of contents #

  1. The Gartner Magic Quadrant
  2. Gartner’s Data and Analytics Governance Platforms reports
  3. Data governance solutions: What to expect
  4. Related Gartner reports on data quality and data governance
  5. Using Gartner’s Magic Quadrant reports for data-driven decision making
  6. Gartner Magic Quadrant for Data Governance: Related reads

The Gartner Magic Quadrant #

The Gartner Magic Quadrant report identifies key players within a specific marketplace. It evaluates products based on their ability to support essential features and commonly expected functionalities, alongside a variety of additional criteria. Based on this assessment, products are categorized into four distinct groups:

  • Leaders: Demonstrate depth across a broad range of common functions. Leaders have typically provided core capabilities for years, understand the changing trends in the market, and push new ideas and features that set them apart from the crowd.
  • Challengers: Understand the current state of the market and have proven they can deliver. Typically, challengers have a few features that are mature and well-evolved. However, they typically lack the breadth or thought leadership of the Leaders.
  • Visionaries: Innovators with a strong understanding of trends and emerging technologies. While pushing the boundaries of their market, Visionaries often lack the market presence, brand recognition, and resources that Leaders have.
  • Niche Players: Specialists in specific industries, geographical areas, or other segments. Niche Players typically serve a specific use case well and can offer pricing advantages. However, they lack the breadth, scale, and strength of their competitors.

Gartner publishes these four categories as a quadrant into which it places each company and its associated offering. The final result is an educational, visual depiction of how each offering stacks up against the other.

Along with the Magic Quadrant report, Gartner publishes a Critical Capabilities report. The Magic Quadrant report covers features but also looks at other factors, such as a company’s completeness of vision, sales rhythms, customer experience, and operations. The Critical Capabilities reports dive more deeply into the features each product offers.

Gartner’s Data and Analytics Governance Platforms reports #

Gartner is expected to release both the Magic Quadrant and Critical Capabilities reports for Data and Analytics Governance in Q4 2024.

Based on previous reports, we can expect the Magic Quadrant report to cover the following areas:

  • Mandatory features: Must-have features for data and analytics governance solutions. These are the features a product needs to implement even to compete at a basic level.
  • Common features: Other capabilities - usually new innovations or developing trends - supported in a number of leading products.
  • Magic Quadrant ranking: A visual plot of where each company falls in the Leaders, Challengers, Visionaries, and Niche Players rankings.
  • Strengths and Cautions. For each vendor, Gartner lists the areas where it stands out - e.g., ease of use, increasing market presence, strong implementation of a key feature, unified/integrated solutions, or strong partnerships. It also lists gaps that might be cause for concern, which can include weakness of certain features relative to other vendors, limited availability (e.g., not available in certain geographic regions), poor support and/or documentation, integration issues, or declining market presence.

Data governance solutions: What to expect #

It’s impossible to say definitively what will be in the final Gartner Magic Quadrant and Critical Capabilities reports for Data and Analytics Governance.

However, some themes emerge from previous Gartner publications regarding both data governance and data quality. These include both Gartner’s publicly available posts as well as research such as its Hype Cycle for Data and Analytics Governance.

A few themes that emerge from this coverage include:

  • Metadata management and active metadata
  • Master Data Management (MDM)
  • Augmented data cataloging
  • Augmented data quality (ADQ)

Metadata management and active metadata #


Metadata, or data that describes data, is critical to both governing data as well as managing overall data quality.

Metadata helps identify the purpose, meaning, derivation, and ownership of data in your data estate. It also enables data lineage, which traces the journey of data throughout a company. Data lineage is critical both for building trust in data as well as fixing data quality and compliance issues at their source.

Metadata isn’t any good unless you can keep it up-to-date. Active metadata leverages open APIs to ensure metadata flows continuously between data systems in a two-way stream. This enables companies to curate recommendations, generate alerts, and automatically make decisions without human intervention.

In its Magic Quadrant for Augmented Data Quality Solutions, Gartner lists active metadata as a common feature. Active metadata also features as a component in many up-and-coming features covered by Gartner in their Hype Cycle for Data and Analytics Governance.

Master Data Management (MDM) #


Master Data Management, or MDM, is a comprehensive method of defining, structuring, and managing the critical data within your organization. Done well, it confers multiple benefits, including better data consistency, improved data quality, and streamlined data workflows.

Gartner lists MDM on the Slope of Enlightenment on its Hype Cycle for Data and Analytics Governance. This means it’s moved beyond its early hype, and multiple organizations are leveraging it to streamline their data governance initiatives. It also indicates that a number of commercial vendors provide supporting features that make implementation easier.

In particular, Gartner says it sees Cross-Enterprise MDM as increasingly critical, as cross-enterprise data governance issues “are increasingly difficult to overcome.”

Augmented data cataloging #


A data catalog enables data discovery and data management, giving you a full view of all the data in your data estate. Running a data catalog is a necessary foundation for data governance.

Augmented data cataloging goes a step further, leveraging Machine Learning and AI to help organizations find and manage data assets. It recognizes that data catalogs are not merely passive repositories of metadata but are active, ML-driven tools that help automate, inform, and improve data management processes.

Gartner identifies augmented data cataloging as a way to drive collaboration, automation, and cost optimization. Gartner recommends investing in solutions that can collect all types of metadata. It encourages customers to leverage this metadata to drive insights that can help mitigate governance and compliance risks.

Augmented Data Quality (ADQ) #


Similar to augmented data cataloging, more vendors are leveraging AI technology to manage data quality. And with good reason. By Gartner’s estimates, poor quality data costs organizations $12.9 million USD yearly.

Augmented data quality (ADQ) leverages AI to enhance data quality and reduce manual effort. Gartner includes a number of features under the umbrella of ADQ, including:

  • Support for multiple personas, such as enabling non-technical business users to use natural language queries
  • Semantic connections
  • Lineage tracing
  • Data engineering-centric tools to enable enhanced monitoring and observability

Gartner recommends establishing comprehensive data cataloging capabilities and then leveraging ADQ procedures to enhance your company’s overall data governance objectives and metrics.

While waiting on the new Magic Quadrant report, we’d recommend reading other relevant Gartner publications related to data governance and data quality. These include:

Data and Analytics Governance Roadmap. A free roadmap document that provides a blueprint for enacting a successful data and analytics governance strategy, with a focus on setting up organizations for success with their AI use cases.

Hype Cycle for Data and Analytics Governance. Gartner Hype Cycles plots new product capabilities and features through a curve that goes through five stages, from the Innovation Trigger to the Plateau of Productivity. It aims to identify when a new capability transitions from hype into practical implementation.

Market Guide for Active Metadata Management. Gartner retired its Magic Quadrant for Metadata Management. It’s replaced it with its new Market Guide for Active Metadata Management. This reflects Gartner’s conviction in the importance of active metadata for not only mapping an organization’s data but making it actionable.

Magic Quadrant for Augmented Data Quality Solutions. Gartner feels ADQ is important enough that it focuses on ADQ tooling as its own set of capabilities. Its Magic Quadrant report is driven by the company’s projection that, by 2025, 90% of data quality tool purchases will be driven by factors such as ease of use and automation.

Magic Quadrant for Data Integration Tools. This Magic Quadrant report evaluates tools for gathering, tracking, and delivering data across a variety of data sources and storage types.

Using Gartner’s Magic Quadrant reports for data-driven decision making #

Gartner’s Magic Quadrant reports thoroughly evaluate their target markets, identifying both leaders and up–and-comers. Used intelligently, Gartner’s insights can help you make data governance tooling investments that will continue to provide business value for years to come.

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