Metadata management: 5 best practices
Finding the right information in your organization’s vast sea of data is no walk in the park. When it comes to efficient and meaningful metadata management, you don’t have to be lost! We gathered for you the top five best practices you need to unlock your data’s power in 2023. By following these steps, you’ll be able to take control of your organization’s data and use it to its full potential. Let’s get started!
What is metadata management?
Metadata is essentially the “data about data.” It’s the information that helps you understand the context, content, and purpose of your data assets. When you have a clear and organized system for managing metadata, you can quickly and easily locate and use the data you need to drive business decisions and achieve your goals. Metadata is generated when data is created, deleted, or updated. Metadata adds context (product title, description, size, filing date, etc.) to actions, making them more efficient.
However, to properly leverage this metadata, companies must carry out metadata management. Otherwise, they are more likely to make poor decisions based on incorrect information and faulty data.
5 best practices for metadata management
Although each data management strategy will be unique to an organization’s specific needs, there are some key tips to follow to ensure your management can weather any storm. Here are DataGalaxy’s recommended practices for making the most of your metadata management:
#1: Set specific metadata management goals and KPIs
Setting metadata management goals and KPIs that align with the organization’s vision is essential for ensuring that the metadata management efforts are closely tied to the overall business objectives. These goals should be specific, measurable, attainable, relevant, and time-bound (SMART). Additionally, it’s important to identify key performance indicators (KPIs) that will help you measure progress toward these goals and ensure that you are making meaningful progress.
#2: Define a data governance strategy
Developing a data governance strategy is crucial for defining the direction and focus of your metadata management efforts. Data governance helps to ensure that the organization’s metadata management efforts are aligned with its overall business vision and objectives. A data governance strategy provides a roadmap for how the organization will manage and use its data and metadata in a way that supports its goals and drives business value.
Without a clear data governance strategy, it can be difficult to determine the direction and focus of the metadata management efforts. This can lead to a lack of clarity and direction and can result in metadata management efforts that are disconnected from the organization’s overall goals and objectives.
Furthermore, a data governance strategy can outline the precise steps that need to be taken to achieve the organization’s objectives through effective governance. This can include establishing policies and procedures for managing and using data and metadata, setting standards for data quality and integrity, and defining roles and responsibilities for data management.
#3: Create a cross-functional data team
Creating a cross-functional team dedicated to managing metadata is key to ensuring a cohesive metadata management approach. A team that includes both business units and IT can help ensure that the metadata process and strategy are aligned with the needs and goals of the entire organization. As business units and departments are often the primary users of data and metadata, having their input and perspective can help ensure that the metadata management efforts are comprehensive and effective. At the same time, IT plays a critical role in supporting and enabling data management and analytics. Having their expertise and input can help ensure that the metadata process is efficient, scalable, and compliant with relevant regulations or standards.
#4: Adopt consistent metadata standards
Adopting metadata standards is essential for ensuring consistency in how metadata is collected, stored, and used across the organization. By adopting standards, you can ensure that all metadata is consistently formatted and easily understandable by all users.
On the other hand, if you fail to standardize your metadata, you will quickly run into problems. For example, it will be harder for other people to understand and use your data, as they may not know what the different fields mean or how the data is structured. This can lead to confusion and errors, making it more time-consuming to work with the data. It can also make it more difficult to analyze or interpret the data, as you may not have all of the necessary information available or may not be able to easily compare it to other data sets.
Here are some examples of metadata standards that could be relevant to your organization depending on your activities and industry:
- Dublin Core: This widely-used metadata standard provides a set of core elements for describing digital resources such as documents, images, and videos.
- ISO 19115: This standard is specific to geographic metadata and includes elements such as spatial and temporal extents, data quality, and resource maintenance information.
- ISO 27001: This standard is a framework for information security management, and includes metadata elements related to information classification, access control, and incident management.
- PRISM: This is a metadata standard for the publishing industry, and includes elements such as title, author, and abstract.
- Data Documentation Initiative (DDI): This is a metadata standard for social and behavioral sciences, and includes elements such as study design, sampling procedures, and data collection methods.
- Open Web Format for Product Data (OWL-PD): This is a metadata standard for describing and exchanging product data, and includes elements such as product features, dimensions, and warranty information.
#5: Deploy a metadata management tool
Deploying a metadata management tool such as a data catalog can greatly facilitate metadata collection, storage, and search. These tools often include features such as metadata repositories, workflow management, and search capabilities, which can help streamline the metadata management process and make it easier for users to find and use the metadata they need.
The benefits of implementing a data management strategy
In conclusion, implementing a robust data management strategy that includes metadata management can bring numerous benefits to an organization. It allows for easier discovery and understanding of the company’s data assets, leading to more efficient and productive work. It also enables the organization to ensure the consistency of its information, strengthen its data documentation for more accurate analyses, and access more qualitative data.
Conclusion
By enabling the reuse of data by all employees, metadata management can save time and allow employees to focus on tasks that add value. Overall, the effort required to build a comprehensive data management approach is well worth it for the numerous benefits it can bring to the organization.
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Still have questions about metadata management? Turn to DataGalaxy to create your company’s data lineage mapping, develop a standardized business glossary, and much more! Check our calendar and select a date that works for you to jumpstart your free 15-day platform trial access and start making the most of your data today!
