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Introducing the Benefits, Precautions, Methods, and Best Practices for Managing Metadata

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Metadata is crucial for managing and effectively utilizing your data assets. Yet, some may not fully understand its benefits or management practices.

This article explains the significance of managing metadata, considerations to bear in mind, and best practices, including steps to start managing metadata effectively.

What Is Metadata Management?

Metadata management involves organizing and recording information about data to support its comprehension, use, and oversight.

First of all , metadata is "data about data." Metadata is data that describes the essence and characteristics of data, and is used to manage and utilize data. For example, information about a file such as its creator, timestamp, file size, data format, and storage location is metadata. This information is essential for understanding, effectively managing and utilizing data.

Metadata falls into several categories, including:

  • Technical Metadata:

Focuses on the technical aspects of data, like database column properties, access permissions, and conversion methods. Information that focuses on the physical aspects of data and represents information about data in IT. This includes database column properties, access permissions, data conversion methods, etc. Database column information, access permission settings, data conversion methods, etc.

  • Business Metadata:

Describes business-related information, such as industry terminology, rules, security settings, undefinitions' describes information related to a business area and includes industry terminology, business rules, security settings, definitions of business terms, etc. Dictionaries of industry terms, business rules, data security settings, business term definitions, etc.

  • Operational Metadata:

Generated during system operations, this includes logs and results that inform system efficiency improvements. Information generated during system operation, including batch job logs, data extraction results, etc., and provides information to improve system efficiency. Batch job execution logs, data extraction results, data lifetime tracking information, etc.

The Importance of Metadata Management

Managing metadata is vital in data-driven businesses for reasons such as data utilization, security enhancement, and accelerated data retrieval. It is fundamental in understanding, utilizing, and governing data. Proper management of metadata is key to leveraging the full potential of data in today's business landscape.

Utilization of data

Metadata management is key to leveraging data. For example, many data-related activities leverage metadata, such as data analysis, decision-making, and business process improvement. Metadata makes it easier to understand the meaning and context of your data, allowing you to maximize the effectiveness of your data, and managing this metadata is key to business success.


Metadata management improves data security. This is to ensure data confidentiality and reduce security risks by incorporating access right sand security information as metadata. Proper metadata management ensures proper access to data.

Rapid data acquisition

Implementing metadata management makes it easier to quickly retrieve the information you need. For example, clarifying the location and attributes of your data will make it easier to access your data. The result is less time searching for data and faster decision making.

As mentioned above, metadata is an essential element in understanding, utilizing, and managing data. In today's data-driven business environment, managing such metadata appropriately is the key to success and maximizes the potential of data utilization.

Five Benefits of Managing Metadata

1. Aggregation of Data

Metadata management centralizes scattered data, clarifying location and attributes, which aids in integration within an organization .Metadata management helps eliminate data dispersion and fragmentation, and centralizes scattered data. Clarity in data location and attribute information contributes to data integration and organization within an organization. The result is more reliable data and more informed decisions

2. Data Quality Improvement

Explicit recording of data meaning and accuracy enhances data quality. Monitoring and improvement are facilitated by metadata, supporting reliable decision-making. Metadata management contributes to improving data quality. This means that the meaning and accuracy of data is explicitly recorded, ensuring data quality is maintained and improved. Metadata also includes data update history and quality information, which helps you monitor and improve data quality. Improved data quality can support reliable decision-making and develop strategic business actions.

3. Efficient Data Retrieval

Metadata management allows for quick data search and retrieval, increasing operational efficiency and leading to faster data analysis and strategic actions. Eliminate the hassle of searching for the necessary data, increasing the speed of analysis and decision-making. Managing metadata allows you to quickly search and retrieve data, increasing operational efficiency

4. Insightful Multifaceted Analysis

By understanding data attributes and relationships, metadata supports comprehensive evaluations and integrations, essential for strategic decisions. Metadata supports multifaceted analysis of data. This means that by understanding the attributes and relationships in your data, you can sophisticatedly evaluate the true value of your data and its potential contribution to your business. Additionally, you can integrate disparate data sources and gain comprehensive insights. Analyzing data from multiple perspectives is essential for strategic decision-making and is the key to competitive advantage.

5. Enhanced Security

Metadata records access rights and personal information, facilitating appropriate data use and monitoring, thus reducing the risk of breaches and ensuring compliance with regulations. Metadata management contributes to improving data security. Specifically, information about data access rights, data flows, and personal information is recorded as metadata to facilitate the appropriate use and monitoring of data. Incorporating personally identifying flags and security policies into metadata ensures proper protection of data, helping to reduce the risk of data breaches and comply with legal regulations.

In companies that have actually developed metadata, employees are now able to search for data independently.

Consider for example atama plus Co., Ltd. that has taken initiatives such as making the entire metadata searchable and allowing anyone to input information into the metadata. As a result, business members with limited technical knowledge or employees with SQL skills but not knowing where specific data is located can now find the data they need on their own.

Considerations in Metadata Management

When managing metadata, it's important to handle personal information carefully, regularly update metadata to maintain quality, and acknowledge the costs and resources required. Metadata often contains sensitive or personal information within the data. For example, photo files have embedded "Exif" metadata that includes personal information such as date and time the photo was taken and location information. Failure to properly manage such metadata can lead to privacy violations and legal issues. Especially when sharing photos and videos on social media and online platforms, it is necessary to check and properly delete Exif information. Even within companies, sufficient care must be taken to properly handle metadata containing confidential and personal information.

Metadata Management Steps

Define Collection Purpose and Targets:

Clearly establish data collection goals to guide collection efforts and avoid data loss or analytical focus dilution. The first step in metadata management is to clarify the purpose and target of data collection. It is important that data collection is goal-based, for example, collecting data to align with business goals such as developing new products, improving security, or analyzing the market. Starting data collection without setting goals increases the likelihood of information overload, data loss, and loss of analytical focus. Set clear goals and provide a clear direction for data collection.

Collect Metadata:

Gather accurate metadata to lay the foundation for data usage and management. Once your goals are determined, collect the necessary metadata. Metadata is important information that describes data and helps it be understood and shared within an organization. Although we may use automated tools to extract metadata from databases, we apply data validation techniques to ensure data reliability and quality. Collecting such accurate metadata is a critical step in laying the foundation for data usage and management.

Organize and Categorize Metadata:

Label, describe, and identify data characteristics for clarity and ease of understanding. Once you have collected your metadata, organize it and categorize it appropriately. Organizing your metadata includes adding labels, providing detailed descriptions, and identifying data characteristics. This makes it clear what the data is and how it relates, making it easier to understand. When organizing, be sure to explicitly describe the hierarchical structure and dependencies of the data. Such organization and classification is essential for effective management and rapid retrieval of metadata.

Maintain Metadata Quality:

Implement controls for accuracy, consistency, updates, and version management to ensure data reliability. Failure to regularly update metadata can reduce data quality and spread misinformation. Managing and updating metadata requires sufficient resources and planning to maintain data accuracy and reliability. Metadata quality control includes accuracy, consistency, updates, and version control. Quality control is essential because poor data quality can lead to incorrect information impacting decision-making and analysis. Regular audits and data cleansing are also part of quality control. Adhering to quality controls ensures data reliability and usefulness and maximizes the use of data assets.

Best Practices in Metadata Management

Define a Data Governance Strategy:

Set SMART goals and KPIs to ensure metadata management aligns with business objectives.

Good metadata management practices start with developing an effective data governance strategy. Data governance is the foundation for ensuring that metadata management is aligned with the organization's vision and ensures data quality and security. Defining a data governance strategy specifically sets specific, measurable goals (SMART goals) and key performance indicators (KPIs) to ensure metadata management aligns with business goals .This allows you to regularly assess your progress and use it to guide your success.

Utilize Metadata Management Tools:

Employ tools to streamline metadata handling and enhance data asset management. Proper use of metadata management tools is essential for effective metadata management. These tools streamline the collection, storage, and retrieval of metadata and help you effectively manage your data assets.

Create a Cross-Functional Team:

Include both business units and IT to ensure metadata strategies meet organizational needs. Managing metadata is more than just a specialized department. It is essential to build across-functional, integrated team that includes business units and IT to support metadata processes and strategies that align with the needs of the entire organization. The combination of business unit insights and IT expertise ensures comprehensive and effective implementation of metadata management.


Manual metadata management poses the risk of human error. Efficient management can be significantly facilitated by using a data catalog. Trocco®, a comprehensive analytics platform support tool, offers a data catalog function that streamlines metadata management, eliminating operational bottlenecks.

Trocco® is a SaaS that aids in the construction and operation of analytics infrastructure, covering areas like ETL/data transfer, data mart creation, job management, and data governance.

TROCCO is trusted partner and certified with several Hyper Scalers