Good data management needs good metadata management. A well-developed metadata management system needs precise and well-documented metadata management frameworks, metadata development, and metadata stores.
What is metadata?
Metadata can be described as information to describe other data, simple examples of metadata can include titles, dates, authors, and keywords to describe datasets. Metadata can provide basic information about data, making working with particular sets of data more efficient. Metadata can be generated manually which could contain more descriptive details, or it could be created automatically containing less detailed basic information.
Why do we need metadata?
Metadata makes it easier to locate relevant information and data. Searches are mostly done through text, for example conducting Google searches. Metadata makes documents easier to find since it captures key information that the document contains. Therefore files that contain audio, images, and video are more difficult to find if there was no text metadata available, by including text metadata files like that will also be easier to locate.
Using metadata to organize resources and information could be extremely useful especially within organizations with growing amounts of data collected and stored. Having organized information using metadata can save time when there is a need to quickly search for pieces of information.
Data is often reused in advancing projects or starting new projects. It is important that the data can still be found and used. Reusing data also requires careful preservation and documentation of the metadata to ensure that it captures enough information.
Many organizations consist of cross-functional and departmental teams where intricate collaboration is required to perform tasks. Metadata can be shared across departments and organizations in an open and secure data environment, metadata can provide the users about what and where the information is held. This also reduces the security and cost implications of migrating data from different systems.
What are the different types of metadata?
There are a few different types of metadata being used by organizations depending on the purposes they serve. The four main types of metadata are descriptive, structural, administrative, and relationship.
Descriptive metadata can be used for the discovery and identification of the different types of information and data stored. Some descriptive metadata can include title, author, and date of creation. Keywords that capture specific characteristics of the information are also considered descriptive metadata.
Structural metadata gives insights into the structure of the data, its format and its assembly. An example of structural metadata can be the table of contents for a book. Structural metadata facilitates interoperability and ensures that with the defined metadata, information can be easily found and accessed.
Administrative metadata can include instructions and guidelines about how to use the data and the data itself. It may list the restrictions on a file, this could include having information about who can access certain information. Administrative metadata has a critical role in database management.
Relationship metadata can describe how data is linked to other resources that could be especially useful in analyzing relational databases. Relationship metadata helps identify important data trends and provides insights into further data analysis.
How to use metadata to manage databases?
Effective metadata management provides crucial insights to organizational databases, fueling their efficient data use and reuse. Below is a proposed process of how to use metadata to manage databases.
1. Define a metadata management framework
Metadata management starts with defining a metadata management framework to provide a foundation for assessing long-term value and should be easily followed and repeated for future purposes. The purpose of defining a metadata management framework must also support and align with the organization’s business goals and vision.
2. Identify the scope of metadata management
Identifying the scope is a way to allocate efforts in the right direction and prioritize important tasks. First, there is a need for you to identify the different use cases for metadata management, this could be for data governance, data analysis, and data visualization. Specify all possible ways you will use the proposed solution and under which situations would you need to follow the metadata management framework that you initially proposed. Along with defining the scope, you must consider the essential requirements and edge use cases.
3. Utilize the right metadata management tool to improve work efficiency
From the metadata management framework and scope that you have established, you can identify the key functionalities that you will need. From there, you can select the best metadata management tool to use to achieve the objectives that you have proposed.
4. Adopt the metadata management standards
Common and across-the-board metadata standards ensure uniform usage or interpretation internal and external to the organization. Metadata standards have varying levels of flexibility and complexity, it is important to identify one that would best suit your organizational purposes and objectives. You can evaluate and update the standards to align the best with your use cases and your organization.
5. Make it a repeatable and ongoing process
Metadata management is not a one-time activity, it requires ongoing monitoring, usage, and updating. Making sure that the metadata management framework and approach you have identified allows for flexibility as your organization grows. It is important to conduct regular reviews of the framework to apply any changes or modifications necessary as databases scales.
Introducing Acho’s metadata management function:
On Acho Studio, we provide a feature that uses metadata to organize, analyze, and collaborate on databases, where we named it “Data Annotation”. You can easily make comments on a shared database for you and your team to view. The users will have the ability to see who made the comment and when the comment was made for easy future references moving forward with a working project.
On Acho Studio, you can make comments on your database. On each column, a yellow mark will appear when you have made a comment.
To make a comment, click the dropdown button after the column field name first. Then click "Annotate". A dialog will pop up. You can write your comment on it along with your teammates in a project.
With proper metadata management tools and framework, working with big data and cross-collaboration within organizations becomes easier and workflow becomes more efficient. Data without metadata to describe its significance can be overlooked and not captured even if the information that it provides is important to an organization’s success.