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In the realm of data management, a revolution is afoot. The arena once dominated by traditional metadata management is now yielding to a dynamic and proactive successor: active metadata.
This paradigm shift is recognized by none other than Gartner, a globally recognized research and advisory firm. Their recent move away from the Magic Quadrant for Metadata Management Solutions to a Market Guide for Active Metadata underlines this shift.
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Let us unpack the nuances of this change, and delve into why Gartner has made this shift. We will also explore ways you can lead the charge in the adoption and implementation of active metadata management.
Table of contents #
- Gartner Magic Quadrant for Metadata Management Solutions: What has changed and why?
- Gartner’s take on active metadata
- Gartner’s warnings on active metadata management
- Atlan’s approach to active metadata management
- Related reads
Gartner Magic Quadrant for Metadata Management Solutions: What has changed and why? #
Gartner, long recognized as an arbiter of technology trends, previously employed the Magic Quadrant for Metadata Management Solutions to evaluate and compare various offerings in the field.
This model served as a guidepost for organizations navigating their metadata management journey. It focused on the management of metadata, tracking what data existed and where, and enabling organizations to catalog, manage, and utilize their data effectively.
However, Gartner has since recalibrated their approach, acknowledging the evolving landscape of data management. As a result, they’ve scrapped the former Magic Quadrant for Metadata Management and replaced it with a fresh focus on active metadata.
Read more → Activating metadata to enable DataOps
This shift signals a recognition of the growing importance of understanding and mapping data flow throughout an organization’s data estate and making it actionable. That’s why active metadata is now an integral part of tools like data catalogs, providing real-time insights into how people use data within an organization.
The new Market Guide for Active Metadata Management elevates the conversation from simple metadata management to the active tracking of data usage. It demonstrates Gartner’s commitment to keeping pace with the increasingly dynamic nature of data management.
Also, read → 101 guide to active metadata management
An overview of Gartner’s shift to active metadata management #
As per Gartner, active metadata management is "a set of capabilities that enables continuous access and processing of metadata that support ongoing analysis over a different spectrum of maturity, use cases, and vendor solutions.”
This focus indicates a transition from static, passive metadata management tools towards more dynamic, actively-engaging offerings.
The primary catalyst for this change is Gartner’s view that metadata management, as a standalone offering, is increasingly becoming irrelevant. The passive and static nature of traditional metadata management tools meant that they were often underused and failed to provide the dynamic insights necessary for contemporary data-driven decision-making processes.
With the rapid changes in data generation, processing, and utilization, these traditional tools struggled to keep pace.
That led Gartner to stipulate that active metadata capabilities should be integral to modern data tools like data catalogs, rather than being treated as separate components.
In other words, Gartner envisions a seamless integration of metadata management into broader data management strategies, facilitating continuous, real-time access to and analysis of metadata.
This shift towards active metadata signifies Gartner’s acknowledgment of the changing data landscape and the need for data management tools to evolve accordingly.
Gartner’s take on active metadata #
Gartner’s recommendations for active metadata management emphasize several elements, including:
- Openness
- Artificial intelligence and machine learning
- Automation
- Workflow optimization
- Collaboration
Let’s explore each element further.
Openness #
Openness is needed to break down data silos and promote greater metadata utility. Openness is no longer optional, says Gartner; it is mandatory.
Artificial intelligence (AI) and machine learning (ML) #
Gartner highlights that advanced techniques such as Artificial Intelligence (AI) and Machine Learning (ML) are crucial to active metadata management.
These technologies provide automated recommendations, extending the functionality of metadata beyond traditional business glossaries and data lineage.
Automation #
In addition to enhancing data lineage and classification, Gartner emphasizes that active metadata management is critical for automating workflows. They enable automated analysis of users, use cases, and situations, allowing organizations to be proactive and agile.
It plays a significant role in automated data governance, streamlining the process of monitoring, maintaining, and enforcing appropriate data usage within an organization.
Workflow optimization #
Data practitioners should also expect to see optimized workflows with active metadata systems. Even for those tasks that fall short of full automation, active metadata can optimize manual workflows for data practitioners.
Collaboration #
Yet another area where active metadata shows its strength is collaboration. Active metadata can support the setup of a cohesive, integrated platform that enables various stakeholders to share, communicate, and collaborate effectively. This reduces data silos and fosters a more data-driven culture across the organization.
Read more → Gartner on active metadata management
As Gartner heralds the transition towards active metadata management, it also raises certain cautionary flags. Let’s see what these are and how to watch out for them.
Gartner’s warnings on active metadata management #
The most notable concern revolves around the challenge of interoperability. In the absence of universal standards, achieving seamless interaction between disparate data systems poses a significant hurdle.
Gartner specifically warns that the lack of established standards can hinder systems from working together effectively. This lack of interoperability can compromise the “openness” that is so critical to active metadata, potentially restricting its ability to accommodate diverse data formats and interact with different applications.
That’s why a holistic approach to active metadata management should include strategies to overcome interoperability issues and create an integrated, effective data management system. And with that, we’d like to introduce Atlan — the only catalog that activates your metadata.
Atlan’s approach to active metadata management #
Atlan is an active metadata platform for modern data teams. It creates a single source of truth by acting as a collaborative workspace for data teams and by bringing context back into the tools where data teams live. Atlan features deep integrations across the modern data stack, including Slack, Snowflake, dbt Labs, Redshift, Looker, Sisense, and Tableau.
Atlan has been featured in Gartner reports on active metadata management, data cataloging, DataOps, and more.
The latest Forrester report on Enterprise Data Catalog for DataOps named Atlan as a leader, receiving the highest possible score in 17 evaluation criteria including Product Vision, Market Approach, Innovation Roadmap, Performance, Connectivity, Interoperability, and Portability.
Atlan also debuted as a leader in the G2 Spring 2023 Grid® Reports for Data Governance, Machine Learning Data Catalog, and Data Quality categories.
Don’t just take our word for it; experience it firsthand. By offering a platform that supports seamless interaction between diverse data systems, we’re working to make Gartner’s vision of effective active metadata management a reality.
Gartner Magic Quadrant for Metadata Management: Related reads #
- Gartner Data Catalog Research Guide — How To Read Market Guide, Magic Quadrant, and Peer Reviews
- A Guide to Gartner Data Governance Research — Market Guides, Hype Cycles, and Peer Reviews
- Gartner Active Metadata Management: Concept, Market Guide, Peer Insights, Magic Quadrant, and Hype Cycle
- The G2 Grid® Report for Data Governance: How Can You Use It to Choose the Right Data Governance Platform for Your Organization?
- The G2 Grid® Report for Machine Learning Data Catalog: How Can You Use It to Choose the Right Data Catalog for Your Organization?
- Data Catalog: What It Is & How It Drives Business Value
- What Is a Metadata Catalog? - Basics & Use Cases
- Modern Data Catalog: What They Are, How They’ve Changed, Where They’re Going
- Open Source Data Catalog - List of 6 Popular Tools to Consider in 2024
- 5 Main Benefits of Data Catalog & Why Do You Need It?
- Enterprise Data Catalogs: Attributes, Capabilities, Use Cases & Business Value
- The Top 11 Data Catalog Use Cases with Examples
- 15 Essential Features of Data Catalogs To Look For in 2024
- Data Catalog vs. Data Warehouse: Differences, and How They Work Together?
- Snowflake Data Catalog: Importance, Benefits, Native Capabilities & Evaluation Guide
- Data Catalog vs. Data Lineage: Differences, Use Cases, and Evolution of Available Solutions
- Data Catalogs in 2024: Features, Business Value, Use Cases
- AI Data Catalog: Exploring the Possibilities That Artificial Intelligence Brings to Your Metadata Applications & Data Interactions
- Amundsen Data Catalog: Understanding Architecture, Features, Ways to Install & More
- Machine Learning Data Catalog: Evolution, Benefits, Business Impacts and Use Cases in 2024
- 7 Data Catalog Capabilities That Can Unlock Business Value for Modern Enterprises
- Data Catalog Architecture: Insights into Key Components, Integrations, and Open Source Examples
- Data Catalog Market: Current State and Top Trends in 2024
- Build vs. Buy Data Catalog: What Should Factor Into Your Decision Making?
- How to Set Up a Data Catalog for Snowflake? (2024 Guide)
- Data Catalog Pricing: Understanding What You’re Paying For
- Data Catalog Comparison: 6 Fundamental Factors to Consider
- Alation Data Catalog: Is it Right for Your Modern Business Needs?
- Collibra Data Catalog: Is It a Viable Option for Businesses Navigating the Evolving Data Landscape?
- Informatica Data Catalog Pricing: Estimate the Total Cost of Ownership
- Informatica Data Catalog Alternatives? 6 Reasons Why Top Data Teams Prefer Atlan
- Data Catalog Implementation Plan: 10 Steps to Follow, Common Roadblocks & Solutions
- Data Catalog Demo 101: What to Expect, Questions to Ask, and More
- Data Mesh Catalog: Manage Federated Domains, Curate Data Products, and Unlock Your Data Mesh
- Best Data Catalog: How to Find a Tool That Grows With Your Business
- How to Build a Data Catalog: An 8-Step Guide to Get You Started
- The Forrester Wave™: Enterprise Data Catalogs, Q3 2024 | Available Now
- How to Pick the Best Enterprise Data Catalog? Experts Recommend These 11 Key Criteria for Your Evaluation Checklist
- Collibra Pricing: Will It Deliver a Return on Investment?
- Data Lineage Tools: Critical Features, Use Cases & Innovations
- OpenMetadata vs. DataHub: Compare Architecture, Capabilities, Integrations & More
- Automated Data Catalog: What Is It and How Does It Simplify Metadata Management, Data Lineage, Governance, and More
- Data Mesh Setup and Implementation - An Ultimate Guide
- What is Active Metadata? Your 101 Guide
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