What Is Data Governance, and How Do Glossaries, Catalogs, and Lineage Strengthen It?
Data governance is a framework that is developed through the collaboration of individuals with various roles and responsibilities. This framework aims to establish processes, policies, procedures, standards, and metrics that help organizations achieve their goals. These goals include providing reliable data for business operations, setting accountability and authoritativeness, developing accurate analytics to assess performance, complying with regulatory requirements, safeguarding data, ensuring data privacy, and supporting the data management lifecycle.
In the field of data governance, business glossaries, data catalogs, and data lineage are essential for effectively managing data across an organization. With an increase in data, finding the right information has become more challenging. Simultaneously, there are also more rules and regulations than ever before. Here's a brief overview of each:
A business glossary is a platform that enables the identification of essential business terms, definitions, concepts, and metrics in a consistent way to ensure universal understanding across the organization.
A business glossary is vital in data governance because it ensures standardized definitions for business terms. This enables clear communication and consistent data usage across the organization. It helps prevent misinterpretation, improves data quality, fosters trust in data, and aids in regulatory compliance. By providing a common understanding of data terms, it also facilitates collaboration, efficient decision-making, and smoother data integration across teams. Without a glossary, organizations risk confusion, inconsistent metrics, and non-compliance with data regulations.
The core components of the business glossary are as follows:
A sample of the business glossary is shown in the table below:
A data catalog is a structured inventory of an organization's data assets, aiding users in discovering, managing, and utilizing data efficiently. This catalog can be created using third-party tools or developed within the organization.
A data catalog is essential for data governance because it provides an organized inventory of data assets. This makes it easier for users to discover, access, and understand data across the organization. The catalog captures metadata, tracks data lineage, and supports classification, which enhances data transparency and trust. It offers a searchable interface, improving data accessibility, reducing duplication, and supporting compliance by ensuring adherence to governance policies. Without a catalog, data becomes hard to find and manage, leading to inefficiencies, inconsistent usage, and potential compliance issues.
The key components of the data catalog include the following:
A sample of the data catalog is shown below:
Data lineage tracks data flow from source through transformation and usage, helping understand data creation, changes, and usage. It ensures data quality, compliance, and impacts of transformations on analytics.
The modern data ecosystem is a complex network of systems and processes that requires a dedicated governance tool for successful navigation. Without data lineage, the consequences can be significant. Here are some key issues that arise from the lack of data lineage:
Data lineage provides the following key benefits:
A sample of the data catalog is shown below:
Some of the most popular companies that support business glossaries, data catalogs, and data lineage are:
Here are the main points to take away from this article:
These three tools work together to enhance data quality, compliance, transparency, and operational efficiency within the framework of robust data governance practices.