Metadata

What is metadata?

Metadata is information that describes other information or, more simply, data about data. Metadata can describe the type of information, how it is structured, where it originated, who is responsible for it, and more. Metadata is used to organize, identify, access, search for, and share data easily, responsibly, and effectively.

Digital music files typically contain metadata that notes the song title, artist name, and album title, with additional metadata potentially noting the genre, tempo, track number, mood, creation date, and more. The metadata makes it easy for a Spotify user to search for a specific song and for Spotify’s servers to return the correct song, for example.

Types of metadata

Metadata comes in four common types:

• Descriptive metadata helps categorize, catalog, and discover data with information such as the title, keywords, summary descriptions, and author. A product’s brand is descriptive metadata. 

• Structural metadata indexes data by defining how data elements are organized. A product’s category, such as “fruit,” is structural metadata.

• Administrative metadata assists with compliance, data governance, data quality, and other critical tasks. An example of administrative data is a data expiration date or creation date that guides data retention.

• Reference metadata provides information about data quality, sources, processing, lineage, and transformations. Reference metadata can influence how data is or is not used for specific applications. 

Why metadata matters

Metadata helps people find, understand, and use data appropriately. Metadata provides the information that enables good data management, data governance, and other practices, especially as organizations generate and gather more and more data.

Metadata is also crucial to data management as it facilitates data organization, storage, searching, and access and plays different roles across the data lifecycle. 

• When data is created, metadata provides key details into how, when, where, by whom, with what applications and devices, and other information that helps categorize and prioritize data.

• When data is organized and stored, metadata provides the information to control access, connect with other data, manage versions, and plan for data movement.

• When data is searched and accessed, metadata makes discovery easier using keywords and categorizations.

• When questions about data arise, metadata captures origins and processing to understand data lineage and provides connections to data stewards and other subject matter experts who better understand the data and its potential applications.

• When data reaches end-of-life, metadata ensures the proper disposition and disposal according to appropriate policies and procedures.

Using metadata, organizations improve data quality by flagging missing or incomplete data, improve compliance by tracking and managing data privacy, sensitivity, and risk levels, and improve transparency using data lineage to understand how data flows through applications and processes.

What is metadata management?

Since metadata is so essential to modern data-driven organizations, they must manage, govern, and put it to work appropriately and responsibly. Metadata management puts metadata best practices into action.

For data consumers, the key issue is data discovery. If users can’t find data, they can’t leverage its value. Organizations then work to make data easily discovered with metadata to categorize the data, provide context and lineage, define sensitivity, access, and usage rules, and more. 

Successful metadata management frameworks also extend metadata to allow data consumers to collaborate with data owners, offer rankings and insights on usage, and submit questions to subject matter experts who know the data best.

Best practices for developing a metadata management program include assigning a team, defining a strategy, adopting standards, deploying a metadata management tool like a data catalog, and scaling across the organization.

How data catalogs use metadata

A data catalog is an organized inventory of an organization’s data assets. It is a centralized repository that stores metadata, such as data sources, formats, quality, lineage, and ownership. Data catalogs help users find, understand, and trust the data they need.

Data catalogs rely on metadata to facilitate data discovery and data governance. Users can find data quickly and easily using a data catalog like a search engine. Organizations can enforce policies and rules to increase compliance and adhere to regulatory requirements. 

Data catalogs differ from metadata management but serve as a solution for metadata management practices by providing a repository for metadata and tools for discovering and capturing data from across an organization.

Where metadata increases AI trust

AI, particularly generative AI and machine learning, relies on large volumes of data for training models and learning. If this data is inaccurate, outdated, incomplete, or of otherwise low quality, AI outcomes will be untrustworthy and AI innovations will not deliver accurate results or expected returns on investment.

Metadata is a foundation for governed, accurate data that AI developers can trust and use to accelerate AI model development and improve AI-driven outcomes.

Alation: Turning metadata into a valuable resource

Alation provides organizations with an intuitive solution for finding, understanding, and trusting data. 

Key features include:

• Surfaces insights like popularity, search relevancy, usage recommendations, and more to guide data consumers to the best use of data.

• Give teams a convenient way to find, understand, and trust data in the tools they use most, with useful metadata information in Slack, Microsoft Excel, Tableau, and more.

• Visualize data lineage, including data flow transformations for compliance and trusted data pipelines, and highlight the potential upstream and downstream impact of data changes.

Alation activates metadata to improve analytics, adapt to change, and enrich a data fabric.

Next steps: Learn more about metadata

Dive deeper into metadata, metadata management, and how a data catalog uses metadata by using the following resources: