Title: Metadata Author: Kriko Published: Jun 1, 2023 Last modified: Jul 7, 2026 --- 1. [Home](https://kriko.io/) / 2. [Glossary](https://kriko.io/glossary) / 3. M Letter # Metadata **Metadata** is information used to describe, explain and provide context for other data. It can contain details about a [data](https://kriko.io/services/data-analysis-insight) source's content, structure, origin, format and conditions of use. In other words, metadata explains what the [data](https://kriko.io/services/data-analysis-insight) represents, where it came from, how it was created and how it can be used. This makes large and complex datasets easier to locate, understand and manage. Metadata helps organise and categorise information. However, it does not collect or analyse large datasets on its own. Instead, it makes the information used in [data](https://kriko.io/services/data-analysis-insight) management, reporting and analytical processes more accessible and understandable. Properly maintained metadata helps [data](https://kriko.io/services/data-analysis-insight) analysts and business users find the resources they need more efficiently. Metadata can be stored in databases, [data](https://kriko.io/services/data-analysis-insight) warehouses, [data](https://kriko.io/services/data-analysis-insight) lakes, content management systems and digital archives. Within a [data](https://kriko.io/services/data-analysis-insight) warehouse, table names, column descriptions, [data](https://kriko.io/services/data-analysis-insight) types, source systems and update dates may all be treated as metadata. This information helps organisations track where [data](https://kriko.io/services/data-analysis-insight) originated and which transformation processes it has passed through. As a result,** [data](https://kriko.io/services/data-analysis-insight) governance**, quality control and data traceability processes can be managed more effectively. Metadata can be divided into different categories according to its purpose. The most common classification includes descriptive, structural and administrative metadata. Technical, statistical, preservation and data provenance information may also be treated as separate metadata categories. The appropriate type depends on the format, purpose and management requirements of the relevant data source. **Descriptive metadata** provides information about a resource's title, subject, author, keywords and content. These details make the resource easier to search for, discover and distinguish from other materials. Digital libraries, websites and content platforms frequently use this type of metadata. For example, an article's title, author and publication date are considered descriptive metadata. **Structural metadata** explains how the different components of a data resource are organised and connected. Relationships between database tables, the order of chapters in a book and the audio and visual components of a video file are examples of structural metadata. This information helps systems process and present complex content in the correct sequence. It also makes relationships between different data components easier to understand. **Administrative metadata** contains management-related details such as creation dates, file formats, access permissions, ownership information and retention conditions. It can show who created a resource, when it was last updated and which users are authorised to access it. Administrative metadata plays an important role in security, copyright management, archiving and information lifecycle processes. It therefore supports more controlled and secure management of digital resources. In summary, metadata is an important component that makes data easier to describe, classify, search and manage. It helps users locate resources related to a particular subject, separate them according to defined criteria and monitor them within a central structure. For organisations, metadata also serves as a management tool that can improve **data quality** and accessibility. An effective metadata structure supports the generation of more accurate and meaningful insights from data. ## Discover it in the dictionary ### Prototype A prototype is an early-stage model created to test a product, service, interface, process or idea. It can also be described as an initial… ### Active Data Warehouse An active data warehouse is a data management system that consolidates organisational information for analytics and reporting while supporting low-latency analysis of current data.… ### HTTPS (HyperText Transfer Protocol Secure) HTTPS stands for HyperText Transfer Protocol Secure. 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