In many ways, data has proved to be of immense value to organizations. There’s no gainsaying that business leaders rely on data in their organizations to make strategic decisions. The information architecture of most organizations is not cataloged, which makes it difficult for data users to find and use data.
Metadata management describes specific aspects of data. Before now, it was limited to using a data catalog to access and find data. Thanks to technology, you can manage all of your organization’s metadata in one environment for elements like a business glossary, business definitions, and business rules. On that note, this article details a complete and comprehensive guide to this form of data management.
Metadata Management Defined
The term metadata management refers to the practice of managing the metadata about data. It attributes meaning to and describes the information assets owned by an organization. With this data management technique, data users can access and use data. What’s more, metadata maximizes the value of data by improving its usability and findability. It also provides data context to enable analysts, and IT teams better understand the administration of data assets.
Metadata is of several types, including structural metadata, technical metadata, reference metadata, business metadata, statistical metadata, and descriptive metadata. Regardless of type, metadata provides valuable information about an organization’s data assets. With this information, business leaders and decision-makers can provide informed solutions to complex data problems. Furthermore, metadata management promotes innovation, team collaboration and mitigates risks.
Metadata Management Framework
Data is unarguably the most important asset of a data-centric organization. Today, many enterprise-level organizations own large volumes of data collected from multiple data sources. It behooves these organizations to find ways of accessing and using their data to gain a comparative advantage over their competition.
This form of managing data plays a critical role in finding and using data. Specifically, it manages the metadata around an organization’s information asset. The main objective of this data management program is to provide top-quality, accurate, and reliable data for data analysis and analytics. By using the insights gained, decision-makers can make data-driven business decisions.
This data management solution works as a SaaS tool. Users can find, use, and manage all their metadata in a single location. The thing is, this form of data management means different things for different groups in an organization. For instance, the people in compliance deploy metadata management solutions to ensure the organization adheres to regulations, such as GDPR.
For IT guys, they’ll leverage enterprise architecture to produce analytical reports and keep historical data. The key takeaway is that enterprise data management provides various teams in an organization with the metadata required to perform their duties optimally.
The Main Benefits of Metadata Management
- Discovery and extraction: It supports the automation of metadata discovery and extraction from on-premises and cloud storage. More so, it serves as a single metadata store for an organization’s technical metadata and business metadata.
- Analytics: Users can leverage governed workflows to gain actionable insights from their analytics programs. Additionally, this form of management optimizes search and collaboration processes. Business users can search and find data using the self-service data catalog feature.
- Optimizes Operations: With a metadata management tool, users can find and use a metadata asset and data lineage to optimize operational efficiency.
- Classification and lineage: It leverages machine learning to classify metadata assets to data lineage and data elements.
- Regulatory compliance: It integrates with data governance to provide support for your compliance programs. As a result, organizations can fulfill regulatory mandates like CCPA, GDPR, and BCBS. An organization’s compliance team can make detailed reports on regulatory compliance efforts and governance policies.
- Digital transformation: It goes without saying that this form of data management promotes digital transformation. The metadata manager can better understand the potential value of information assets in an organization. It also boosts the speed of data impact analysis.