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Metadata management

Table of Contents

What is metadata management?

Metadata is data about data itself—it gives information about data like source, structure, who created it and modified it, instructions on how to use it, and more. Metadata management is the process of organizing, managing, and updating metadata in a central repository. Metadata management is a critical part of data fabric architecture, which is about integrating data storage from all sources and environments. 

From enabling data discovery and data literacy to making data easier to consume, metadata plays a huge role in data architecture.

Components of metadata management

Metadata management is more of a practice than of a platform or a framework. It could be followed by any platform and governed by centralized regulatory frameworks. Though it’s not a platform itself, there are certain tools and parts to help organizations manage metadata. Some of the features and components of metadata management are as follows.

Metadata repository: The centralized storage to organize and manage metadata—also can be called a single source of truth for metadata.

Metadata catalog: This is the metadata index with descriptions and details about your data. Often, you could perform a search or even categorize metadata.

Governance policies: The set of frameworks and policies to manage metadata along with everyone’s roles and responsibilities and maintain data consistency across all roles and use cases.

Integration tools: Systems that you use to connect metadata with other data platforms, databases, and other systems to keep your metadata up-to-date.

Quality management processes: These are unique sets of processes that ensure the reliability, accuracy, and usefulness of metadata. 

Though metadata management is platform-independent, there are some platforms using which you could manage it. Some of them include Microsoft Purview, Informatica Metadata manager, etc.

Why is metadata management important?

Some benefits of metadata management include:

  • To improve data quality: Can control data quality and consistency issues like duplication and errors and maintain them up-to-date for end users, BI, and AI systems.  

  • Easy data discovery, no matter how complex your data systems are: Allows business users to find their required data assets much faster. This quick data discovery helps large organizations where data is dispersed across teams and geographical regions.

  • Better risk management: A transparent guidance through metadata to handle sensitive data with care and ensure strong security measures. Can achieve no security issues and breaches and be more vigilant about regulations.

  • Seamless data integration: Metadata guides you to carry out error-free and transparent data merging and ingestion, even if there are multiple sources and platforms.

  • Better data governance: metadata management helps with data lineage, which is the ability to trace back to the root of any data asset, helping with auditing and compliance. With strict metadata standards, data consumers and stewards better understand the data. This means correct usage, better access controls and strict adherence to regulations like GDPR, HIPAA, SOC, etc.

  • Allows decision makers to use data more efficiently: Knowing who created it, who modified it, and what kind of transformations the datasets went through, decision makers can make more informed decisions. 

  • Reduced efforts on data management: IT and data teams could spend less time with data management. With proper metadata management, they could focus on increasing time to insights and cost savings. 

Start your metadata journey 

It’s assumed that the amount of data an organization handles can go beyond petabytes of volumes. Processes like metadata management are integral in such cases so data and IT teams could breathe and handle data management like a breeze. It also makes the consumers and end users of data aware and accountable of assets they have to simplify decision-making processes and run day-to-day operations with ease.

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