Metadata management tools are solutions that add useful information to data stored in an enterprise environment. Thanks to metadata management, information is easier to search, locate, and understand. Such tools add meaningful context to raw data so that even non-IT members and organizations can access it.
But first, let’s talk about metadata a bit. Metadata is structured reference data that helps to sort and identify attributes of data it describes. It not only makes data easier to find but also to use and reuse different blocks of information.
There are many different types of metadata, but in business terms, we usually talk about:
Technical metadata: Provides information on the format and structure of data.
Business metadata: Defines business terms, rules, sharing practices, etc.
So where to start looking for a great metadata management tool?
#Features That Every Metadata Management Tool Should Have
Data asset extraction, aggregation, and cataloging
Whenever a document, file, or other digital information asset is created, modified, or deleted, metadata is created, too. Your metadata management tool should be able to harvest (extract) metadata across your asset landscape, from both internal and external data sources.
However, extracted metadata is often incomplete, or comes with missing or invalid attributes. In this case, your tool creates (aggregates) additional metadata and links it to your digital resources.
Ultimately, a capable metadata management tool creates a complete detailed and organized inventory of your data assets by collecting and arranging metadata descriptions. These catalogs help data consumers search and retrieve data as they help connect business context to actual data and its location.
Data context management
Context is a key to data discoverability. Even when it comes to seemingly most straightforward business terms, different contexts can lead to different perceptions of data.
For example, the concept of “client” can have different approaches, depending on the team. The sales department will use the term for the company as a whole and is primarily interested in accessing client data through their sales tools to move clients through the funnel. On the other hand, IT would be interested in strictly technical aspects of the term, such as new clients onboard or clients who haven’t renewed their maintenance contract.
A metadata management tool must be able to discern between different data contexts to provide a seamless experience at every organizational level.
Data asset governance
This is an essential element of data management that controls the complete information lifecycle, regulates its usage, and ensures its availability, quality, security, etc. Data governance is critical for every business operation because only well-organized metadata can give a holistic view of the organization data.
Data integration and integrity control
The solution you choose must also be capable of combining data from multiple sources into a single repository. However, the same functionalities can also be used to support decision-making, improve communication, and increase efficiency. Data integrity control, on the other hand, helps prevent data corruption and ensure the data is properly processed.
Collaborative and group functionality
The platform should enable communication and sharing channels to support connectivity between different departments and teams. Collaborative functionalities might include workflows, stewardship, version control, and audit trails.
User access control and authorization
To establish and maintain adequate data control systems that ensure the appropriate authorization, security, and accountability.
#Enterprise Metadata Management Tools
Hygraph is a native Headless CMS that is designed to solve traditional content management problems using GraphQL. Thanks to the API-first architecture, Hygraph can access content from multiple platforms.
As a result, Headless CMS is more secure because it provides a single GraphQL endpoint for your application or website to interact with. GraphQL also allows for faster loading of content, which translates to a significantly smoother performance for your users.
While Hygraph currently lacks the extensibility and flexibility of some of the tools on this list, it shares important aspects with top-of-the-line metadata management platforms.
It allows users to pull data from distributed data sources, provides the UI for easy metadata editing (zero-code required), and provides a single GraphQL API so users can use all the data on any frontend.
A Federated Content Platform like Hygraph allows content editors to ingest, edit, and review the metadata no matter where they keep the other information. The REST or GraphQL API can pull this information to Hygraph. From there, users can distribute it to virtually any frontend.
Why should you consider Hygraph?
- Pulls data from distributed data sources to be used on any frontend
- Secure design as your frontend interacts with one GraphQL endpoint
- GraphQL does all the queries so fewer round-trips to the content API are needed
- Fast and smooth performance
The tool supports powerful data governance and cataloging capabilities designed to harvest and manage data across an organization. Collibra is a collaborative platform for managing metadata that focuses on group interactions where user roles are established for data ownership and consumption.
Collibra works with emerging digital technologies like the Internet of Things (IoT), artificial intelligence (AI), and machine learning.
Created with business end-users in mind, Collibra acts as a searchable repository for users who need to understand how and where data is stored and how it can be used.
Why should you consider Collibra?
- Highly flexible and configurable
- Applicable to a range of industries
- Uses a ticketing approach to establish itself as the system of record for data
- The vendor offers numerous resources and on-demand webinars
Informatica packs a comprehensive, unified, view of metadata, business context, data quality, relationships, tagging, and usage. The platform appeals to a wide array of users, including data analysts, data engineers, data scientists, and data stewards.
It comes with tools for business, technical, and operational metadata management, semantic search, and browsing, end-to-end lineage, data relationship discovery, and impact analysis.
Using Informatica, enterprises can tap into four major categories of data including business (glossary terms and governance processes), operational and infrastructure (time-stamps and run-time stats), technical (database schemas, mappings, and code), and usage (user ratings and comments).
Why should you consider Informatica?
- A powerful and highly flexible approach that focuses on information governance and analytic
- Applicable for a range of infrastructures and industries
- End-to-end approach and robust glossaries
- Ambitions company that keeps expanding its platform and features
Oracle features three metadata management solutions: (1) Oracle Enterprise Metadata Management (OEMM), (2) Oracle Data Relationship Management (DRM), and (3) Oracle Enterprise Data Management Cloud. This way the product covers data requirements for both Oracle and non-Oracle environments.
Oracle enables interactive searching and browsing of the metadata as well as providing data lineage, impact analysis, semantic definition, and semantic usage for any metadata asset within the catalog.
Why should you consider Oracle?
- Oracle apps can harvest, process, and catalog metadata across a range of platforms and frameworks
- Delivers interactive searching and browsing of metadata
- Integrations with business continuity, data movement, data transformation, data governance, analytics, catalogs, and streaming
This platform offers four solutions for metadata management: (1) SAP PowerDesigner, (2) SAP Enterprise Architecture Designer, (3) SAP Information Steward for metadata management, and (4) SAP Data Hub. The focus here is on delivering powerful capabilities for diverse on-premises and cloud-based systems.
Users can import metadata from other tools to create reporting and monitoring systems for data migration and data valuation.
SAP puts focus on delivering powerful capabilities for diverse on-premises and cloud-based systems.
Why should you consider SAP?
- SAP Data Hub able to manage both active and passive metadata through flexible coordination
- Supports numerous sources and file types
- A wide array of use cases and personas
The Erwin EDGE Portfolio platform combines data governance, enterprise architecture, business processes, and data modeling. The product comes as a managed service that enables users to discover and collect data, as well as to structure and deploy data sources by linking physical metadata for specific business terms and definitions.
In other words, Erwin helps businesses learn what data they have and where it’s located. Erwin can import metadata from data integration tools, as well as cloud-based platforms, and can evaluate complex lineages across systems and use cases.
Why should you consider Erwin?
- Data governance from anywhere with end-to-end lineage
- Dynamic impact analysis
- Automated data intelligence
- Enterprise collaboration
- An accurate, real-time platform for holistic decision-making
This company’s Data Catalog solution delivers automated data inventory within a highly searchable catalog, supported by a powerful recommendation engine. Using this approach, Alation appeals to both data scientists and business users.
The platform is free from technical jargon and promotes a best-practice approach using collaborative endorsements and warnings.
Instead, it relies on conversations and wiki-like articles that capture knowledge and guide newcomers to appropriate subject-matter experts.
Why should you consider Alation?
- Support for a number of key metadata management tasks such as data valuation, the use of active metadata and trust models for decision-making, and proprietary frameworks.
- A wide array of use cases and a high level of flexibility.
- Formidable collaborative tools that allow groups and users to share information and insight derived from raw data.
Alex Solutions is a marketplace for enterprise data using a robust and highly flexible data catalog, a customizable business glossary, intelligent tagging, and policy-driven data quality that is executed through detailed data profiling and machine learning.
The tool features the world’s largest variety of out-of-the-box metadata scanners that can be configured to harvest a broad variety of metadata including usage information, sensitive data detection, end-to-end lineage, and data profiling data.
Why should you consider Alex Solutions?
- Supports use cases and regulatory requirements across a range of industries
- Appeals to different user groups, like data scientists, analytics specialists, regulatory executives, and privacy and security specialists.
- High level of automation and ability to capture end-to-end data lineage
IBM’s InfoSphere Information Governance Catalog comes with a wide set of tools and functionalities that enable metadata management. This includes a collaborative authoring environment, where users can create a central catalog of enterprise-specific terms, including relationships to data assets, and filters for understanding lineage and data relationships.
You can import metadata into the repository from multiple sources, export metadata by various methods, and transfer metadata between design, test, and production repositories. Changes that users make in the repository are automatically made throughout the suite as well.
Why should you consider IBM?
- Powerful tools for browsing and searching for terms and categories
- Unified Governance and Integration Platform
- An open framework for metadata management
MANTA is a unified data lineage platform that allows users to map all information flows to privacy and a complete overview of their data pipeline. The tool displays the data origin and its journey through all data processing systems to you.
MANTA has the ability to automatically update lineage whenever necessary and to show data flow in a clear and understandable user-friendly way. Its time-slicing feature allows you to see how the system looked in the past at the time of the selected scan and understand how the lineage has developed or what has changed.
Why should you consider MANTA?
- Automate data lineage collection
- Enhance your data governance tools
- Eliminate reporting discrepancies
- Scan even the siloed environment
Offers an on-premise data catalog and governance toolkit that can crawl databases, data lakes, and back-end systems to create a smart catalog of the information. OvalEdge comes with built-in governance tools that help define a standard business glossary, data assets, PIIs, and limits access by various roles.
The platform’s AI and advanced algorithms automate tasks that allow organizations to streamline data access, improve data quality, and encourage adoption.
Like other tools on this list, OvalEdge has a role-based security system in which you can assign roles to users and data sources.
Why should you consider OvalEdge?
- API support
- Metadata propagation
- Auto Lineage functionality
- Collaboration tools
An enterprise-grade semantic platform that allows companies to enrich data, extract facts, and harmonize information sources. This platform offers a model-driven, rule-based approach that improves the capabilities of your existing technologies.
Smartlogic collects and analyzes diverse data to reveal targeted contextual data for tasks such as improving customer experience, contract lifecycle management, records management, data and text analytics, information security, process automation, and regulatory compliance.
These functionalities make Smartlogic a popular choice for a number of industries including healthcare, finance, medical, and manufacturing. The tool is designed for end-to-end governance, and privacy compliance, and features fast and reliable analytics.
Why should you consider Smartlogic?
- Rule-based classification and NLP
- NLP and semantic techniques
- Enhanced information governance
- Process automation
- Scales to manage the volume of your organization
Implementing a metadata management tool is the first step towards creating a modern data stack and achieving the granularity you need from your sources.
To this end, your data assets need to go through a process of data extraction, data aggregation, data transformation, cleaning, and more. The problem is that in most cases each of these steps requires a separate tool.
However, if you choose a comprehensive metadata management tool, you’ll be able to streamline all your data activities and transform raw marketing and sales metrics into actionable insights.