What is Metadata Management?
Metadata management is the administration of metadata for other types of data, a component of data governance in which organizations create rules and processes to govern, maintain, and use metadata for reporting and analytics.
Metadata management is the administration of metadata for other types of data. It is a crucial component of data governance. During metadata management, organizations determine how to govern and maintain metadata and create rules, processes, and protocols for the use of metadata. The end goal is better metadata administration, where organizations successfully use metadata to locate data for reporting, analytics, and other processes.
How Does Metadata Management Work?
Organizations manage metadata in different ways, combining it with other techniques such as Master Data Management (MDM). One of the most successful ways to manage metadata is to extract the data from various sources, transform it into readable formats, and load it to one destination for reporting and analysis. (A process called Extract, Transform, Load (ETL)). When metadata has undergone the ETL process, organizations can use it more effectively.
Tools like Integrate.io extract raw metadata from sources such as data lakes, data warehouses, and other systems, transform it into the correct format for reporting, and load it into a centralized destination. This automates much of the process and allows even the smallest of organizations to manage metadata, even if they don't have data engineering or coding knowledge. (Integrate.io, for example, requires no code whatsoever.)
When is Metadata Management Used?
Metadata management lets organizations gather, organize, and maintain metadata from various sources. By doing this, organizations can:
- Locate specific datasets much easier
- Correct/update data
- Delete damaged or duplicated data
- Add context to raw data
- Generate valuable insights from data
- Improve data quality
Organizations generate data every single day, but much of this data lacks context. Metadata provides meanings and connections to datasets, allowing organizations to locate and explore the data they require for projects.
Without metadata management, organizations might not be able to view relationships between data or draw conclusions about data.
Metadata Types
In a metadata management context, there are two main types of metadata:
- Technical metadata: Metadata that describes the technical features of IT systems, such as descriptions of tables, columns, and values.
- Business metadata: Metadata that describes business processes, such as administrative functions.
Metadata management governs technical and business metadata.
FAQ
Frequently asked questions
Clear answers to the questions teams ask when evaluating Integrate.io.
How does metadata management work?
Organizations manage metadata in different ways, often alongside techniques such as Master Data Management. A common approach is to extract metadata from various sources, transform it into readable formats, and load it to one destination for reporting and analysis using an ETL process.
What can organizations do with managed metadata?
Managing metadata lets organizations locate specific datasets more easily, correct or update data, delete damaged or duplicated data, add context to raw data, generate insights, and improve data quality. Without it, organizations may struggle to see relationships between data or draw conclusions from it.
What are the types of metadata in a management context?
Metadata management governs two main types: technical metadata, which describes the technical features of IT systems such as tables, columns, and values, and business metadata, which describes business processes such as administrative functions.
Need help with your data integration?
Our team of experts is ready to help you build reliable data pipelines with Integrate.io.
Talk to an Expert
