Learn about the concept of metadata, metadata storage and metadata management. And why it matters.
Metadata management gives meaning and description to your organization's information assets. Metadata management requires a well-defined strategy, strong governance and proper integration across systems and processes. The aim is to promote interoperability between diverse systems.
Effective metadata management is like the perfect golf swing."
To get metadata right, organizations need to define and identify metadata requirements based on the nature of their data assets, objectives, and industry standards. Achieving this requires first-hand thinking, rather than just creating technical solutions to manage metadata silos.
Metadata means "data about data". For example, metadata defines whether a "date" refers to a fruit of the date palm or a numbered day in a month. Examples of business metadata include business definitions and descriptions such as glossaries, data quality rules, wikis and report annotations. Operational metadata includes information about how and when data was created or transformed.
Metadata enables organizations to navigate their data landscape more safely and successfully by providing valuable information about the data, such as its source, integrations, location, format and meaning. This helps to understand the data and its characteristics, which is essential for making informed decisions and proactively resolving data-related issues and challenges. A concrete example of utilizing metadata for security is implementing data classification and labeling systems within the organization. This allows for the identification of sensitive data, such as personally identifiable information (PII) or financial data. By taking this proactive approach, the organization can enforce data access controls, implement necessary security measures, and ensure compliance with data protection regulations.
Just as golfers act on hearing the word 'fore', organizations can use metadata to proactively address data challenges.”
Metadata can be used to track data quality metrics and monitor data quality over time. By linking metadata to data quality rules and measurements, organizations can identify and address data issues in a timely manner, improving overall data quality. For example, suppose an organization wants to assess the accuracy and reliability of its data sources. By using metadata, they can create data lineage and data profiling reports that provide valuable insight into the origin, transformation and quality of the data. This enables data stewards to identify any data quality issues, such as inconsistencies, duplicates or missing values. Armed with this information, organizations can take corrective action, such as data cleansing or refining data integration processes, to improve overall data quality.
Data lineage - a documented trail of data flows - is a critical component of effective data management, ensuring transparency, quality and compliance.
Metadata storage plays a critical role in organizing and structuring the different types of data within an organization. It helps to maintain the integrity and reliability of the associated metadata, ensuring its reusability and consistency across different systems and processes within the organization.
Metadata storage is like the golf bag that organizes your data clubs. Just as a golfer selects a specific club from his bag for each shot, metadata storage allows users to retrieve and access data types efficiently and accurately.”
The benefits of metadata storage are many, including facilitating data organization, improving data quality, enabling data discovery and analysis, ensuring compliance, and enhancing knowledge management within the organization.
In large organizations, it is often the case that no one has a comprehensive understanding of the IT landscape. This lack of knowledge is a major challenge to the holistic management of data, information and knowledge. Coordinating the storage of metadata can partially address this issue by providing a more robust, comprehensive and automated view of the IT landscape.
Metadata is scattered across a wide range of tools and technologies, including data catalogues, tool-specific metadata stores, file and database management systems, and independent metadata repositories.
Metadata storage is an area where many metadata management issues exist.
Metadata management is an essential business practice aimed at effectively handling the metadata associated with data. This discipline gives meaning and description to information assets.
Just as keeping score in golf is critical to tracking progress and improvement, metadata management provides a systematic way to measure, track and improve the quality, consistency and availability of metadata.”
The business benefits are numerous: effectively managed metadata facilitates the discovery and accessibility of data. This improves productivity, decision making and collaboration. Second, well-managed metadata enables organizations to identify and resolve data quality issues, minimize duplicate or redundant data, and maintain data integrity. Third, metadata management supports data governance efforts by providing visibility and control over data assets. Accurate and well-documented metadata helps enforce data policies, ensure regulatory compliance, and mitigate privacy and security risks. Fourth, well-managed metadata facilitates data integration and enables interoperability across disparate systems and platforms. Metadata management can streamline data analysis processes.
From a cost control perspective, metadata management helps optimize the costs associated with data storage, processing and maintenance. By identifying unused or redundant data assets and understanding data dependencies, organizations can rationalize data storage and computing resources, reducing unnecessary costs.
In summary, by using metadata effectively, organizations can unlock the value of their data assets, drive greater efficiencies and make informed decisions based on accurate and reliable information.
Well-managed metadata ensures the longevity and adaptability of data assets. By documenting data definitions, context and transformations, organizations can future-proof their data, making it easier to understand and use as technologies, systems and requirements evolve.
Notably, metadata management tools can automatically capture and maintain data lineage information. This helps organizations understand how data flows across systems and processes and facilitates impact analysis when changes are made. In addition, metadata controls and rules can help identify inconsistencies, errors or anomalies in metadata, allowing organizations to take corrective action and maintain data integrity.
Where to start? Start by identifying the specific metadata that is most relevant and useful to your organization’s data management and business needs. This includes determining what context, attributes and relationships should be captured and stored as metadata. Let's tee off and roll out the real value of data!
Sirpa is dedicated to creating business value for customers and enabling growth through data from a strategic perspective. She has more than twenty years of experience in banking and finance in various roles within investment banking (M&A), corporate and industry analysis, rating and large data sourcing and platform integration projects.
In her current role as Head of Data Management Finland at Tietoevry Tech Services, she advises customers on data and data management related brainstorming, especially in connection with cloudification. Her focus is on helping customers do better business through a strategic approach to digitization and the use of data.