For years, companies worldwide have worked constantly to take advantage of the data they collect. They use data to improve operations, identify new opportunities, communicate effectively with customers, and enhance hundreds of other applications.
Finding data to collect and store isn’t a problem – many organizations are buried in it. But understanding what data you have and how to use it can be a big challenge. That’s where metadata comes in.
What is Metadata?
Metadata is information that describes data. Metadata makes it possible to connect data from across an enterprise by providing details such as the data’s format, age, source, and structure. Data professionals turn to metadata management tools to make sense of their data and maximize its value to an organization.
Think of metadata as a roadmap that helps you navigate the vast amounts of data your organization acquires. Without a structure to manage the metadata effectively, much of data’s value would be unrealized.
Metadata enables data governance, making it possible to establish and enforce rules about data security, quality, and regulatory compliance. It also enables integration and consolidation, allowing your organization to connect data from disparate sources, combine data, and eliminate duplicates.
Data isn’t much good if you can’t find it. Metadata management techniques allow systems to locate and organize data based on its attributes, making it easier to extract and use the right information at the right time.
What are the different types of metadata?
Metadata plays a crucial role in managing and understanding data within a business context. By categorizing and organizing data attributes, metadata provides valuable context and enhances the usability of information. Here are some key types of metadata commonly encountered in business settings:
Descriptive Metadata: Also known as simply “descriptive information”, this type of metadata focuses on providing information about the content and characteristics of a data asset. It includes attributes such as titles, descriptions, keywords, and tags. Descriptive metadata helps users understand the purpose, relevance, and context of the data, facilitating efficient search and retrieval.
Technical Metadata: Technical metadata encompasses technical details about data, including file formats, data structures, data types, and data source information. It aids in understanding the technical aspects of data storage, format compatibility, and integration with different systems. Technical metadata ensures that data can be processed and interpreted accurately and efficiently.
Administrative Metadata: Administrative metadata refers to information related to the management and administration of data assets. It includes details such as ownership, access controls, creation and modification dates, version history, and usage rights. Administrative metadata helps in ensuring data governance, compliance, and security, while also facilitating proper data lifecycle management.
Structural Metadata: Also known as “Structural information”, structural metadata defines the organization and relationships between different data elements within a dataset. It describes the logical structure, schema, and interdependencies of data components. For databases, structural metadata specifies tables, columns, primary keys, foreign keys, and relationships. It assists in data integration, data modeling, and data transformation processes.
Operational Metadata: Operational metadata focuses on capturing information about the usage and performance of data assets within operational systems. It includes details such as data access patterns, query history, data lineage, and data transformation processes. Operational metadata provides insights into data usage patterns, optimization opportunities, and troubleshooting in real-time operational scenarios.
Understanding the different types of metadata is crucial for businesses aiming to effectively manage and leverage their data assets. By harnessing the power of metadata, organizations can improve data discovery, ensure data quality and accuracy, enhance data governance, and unlock the full potential of their data resources.
Operational Metadata vs. Master Metadata
Use operational metadata when you need to know technical information about the data. Operational metadata describes data processing details such as how the data is used, who used it, and how the data was loaded or transformed.
“Master metadata”, on the other hand, is not a commonly used business term when it comes to categorizing metadata. The term may be used in some contexts to simply refer to the centralized repository of metadata maintained by an organization. It may also be confused with “master data”, a term that refers to core business data entities such as customers, products, or locations. The effort that goes into managing the metadata associated with these entities is a part of the Master Data Management process.
In general, metadata can be classified into different types such as descriptive metadata, technical metadata, administrative metadata, and operational metadata.
Benefits of Metadata Management
By implementing robust metadata management practices, organizations can realize numerous benefits that contribute to improved data quality, governance, and decision-making. Here are some key benefits of metadata management:
- By capturing and documenting metadata, organizations can establish data quality rules, standards, and validation processes, ensuring data accuracy, consistency, and integrity.
- Metadata management supports data governance initiatives by providing a clear understanding of data lineage, ownership, and usage rights, enabling effective compliance, risk management, and accountability.
- Metadata management fosters collaboration across teams and departments by providing a common language and understanding of data elements, facilitating effective communication and knowledge sharing.
- Metadata management helps organizations manage data throughout its lifecycle, from creation to retirement, ensuring proper versioning, archival, and disposition of data assets.
Organizations should establish clear metadata management strategies, utilize appropriate metadata management tools and technologies, and foster a data-driven culture that values the importance of metadata in data management initiatives. By doing so, businesses can maximize the value of their data assets and stay ahead in the competitive landscape.
Essential capabilities of a Metadata Management Tool
A robust metadata management tool is instrumental in efficiently capturing, organizing, and governing metadata across an organization’s data landscape. Here are some essential capabilities to look for when selecting a metadata management tool:
- Data catalog. An effective metadata management tool should include a user-friendly data catalog, allowing users to search and explore metadata assets efficiently. It should provide advanced search capabilities, filters, and tagging options to facilitate data discovery and understanding.
- Metadata Lineage and Impact Analysis. The tool should enable the visualization and tracking of metadata lineage, depicting the origin, transformations, and relationships between different data assets. Additionally, it should support impact analysis, allowing users to understand the potential consequences of changes to metadata or underlying data elements.
- Business Glossary. An essential capability of a metadata management tool is the inclusion of a business glossary. This allows organizations to define and manage business-specific terms, abbreviations, and acronyms, ensuring consistent and accurate understanding of data across the organization.
- Data Governance and Compliance. The metadata management tool should offer features that support data governance and compliance initiatives. This includes capabilities to define data policies, enforce data standards, manage data privacy and security rules, and facilitate regulatory compliance such as GDPR or CCPA.
An Option: SAP Information Steward Metadata Management
SAP Information Steward’s Metadata Management module stores metadata in a central location, offering access to the information from a variety of information systems throughout the enterprise. It allows users to search and browse the metadata and set up relationships between objects. The module facilitates auditing, usage analysis, and data visualization.
SAP’s metadata solution allows users to add annotations and custom attributes, enabling the metadata to match unique business requirements. Integration with Information Steward Metapedia, a business glossary of data definitions, helps to build data literacy in your organization.
