Metadata is information that provides critical context for data. It makes data easier to find and understand, enabling faster, more efficient business operations.
Metadata can be embedded into data files or stored externally in the original database in a metadata repository/ data catalogue/dictionary. Either approach has its pros and cons.
1. Define Scope and Roles
Metadata is an essential aspect of data management and enables organizations to leverage information to support different business functions. It also helps to create a context for data and makes it easier to locate and organize for use by various users.
There are several types of metadata, each providing its own set of benefits to data management. For example, technical metadata includes information about the format and structure of data, such as its data model or data lineage. Business and content metadata defines terms like business rules, keywords, content habitat, and more.
Developing a metadata policy that sets out standards for capturing, storing, and managing metadata is essential. This can include defining data vocabulary and taxonomy, identifying key stakeholders, and developing a consistent approach to data definitions. Having metadata policies ensures the consistency of data definitions and terminology across your organization, avoiding confusion and misinterpretation. Additionally, it will help to ensure compliance with regulatory and industry standards.
2. Determine the Functionality Your Organisation Needs
Effective metadata management systems can help organizations better understand data and the context around it. This allows them to find and use the information they need in a more effective manner, resulting in faster project delivery, improved performance gains, and greater overall business value.
A metadata strategy should address the needs of data analysis, data quality, data governance, and compliance, both now and in the future. It should also support data search and discovery, which can empower non-technical data users to access the data they need quickly and easily.
Metadata is usually created manually or automatically, containing basic information about data, such as the file type, creator, size, and more. It also contains technical information, such as error logs and data retention rules.
Effective metadata management makes a company’s trove of data discoverable, measurable, and accessible to all users across the organization. This allows data scientists to spend less time cleaning or fixing inconsistencies between different data source formats and systems utilizing the information. It can also save companies a significant amount of money by avoiding redundancy and excess costs in data definitions across systems.
3. Choose the Right Tool or Tools
Metadata helps us discover and work with digital resources by tagging them. The metadata provides a description of the content, such as its date and location, so that we can link it to other relevant information, including keywords.
Whether it’s created manually or automatically, metadata can make the data easier to find and use. It can also help us categorize the information.
When selecting a tool or tools to store and manage your metadata, it’s important to choose one that fits your organizational needs. It should support the data analysis, data quality, and data governance requirements you have today, as well as those you will need in the future.
The right tool for your organization can also provide valuable insights into your data warehouse, helping you prioritize and channel maintenance efforts to the most critical data assets. It can help you determine which tables are most used, which queries take the longest to run, and more.
4. Define Standards
The standards you choose to implement for your metadata storage and management will help you ensure that all metadata is consistent and easy to understand. This will help employees easily find information they need and help you make more informed business decisions.
Metadata is a form of knowledge about data assets and is used to describe, identify, link, structure, and record how they should be managed over time. This knowledge can be derived from data objects or can be compiled and enhanced over time in manageable phases, as with the creation of an archival finding aid or a digital asset catalog.
Various perspectives on metadata have developed within the library, archives, and museum communities over the years. Some focus on a comprehensive conception of what metadata can do.
Others are more specific to particular user groups and use cases. For example, disciplinary metadata standards can address the needs of teachers and students for specialized searches. Similarly, preservation metadata standards can be designed to enhance the ability of machine search tools to interpret digitized materials.