Introduction

Blindata’s Metadata Management Tutorials and User Guides serve as your comprehensive resource to navigate and harness the full potential of our metadata management capabilities. In this space, we provide step-by-step instructions, best practices, and insights to empower you in effectively managing, organizing, and extracting value from your metadata.

Blindata’s metadata management approach is built on a three-layer architecture that enables comprehensive governance and discovery across your organization’s data landscape. This model provides a structured framework for managing both business and technical metadata, ensuring semantic consistency, interoperability, and effective data product lifecycle management. For a deeper understanding of the enterprise architecture principles underlying this model, please refer to our enterprise architecture blog post.

Knowledge Layer: Glossary and Ontologies

The Knowledge Layer forms the semantic foundation of Blindata’s metadata management model. This layer encompasses the Business Glossary and ontologies, which together create a shared vocabulary and knowledge graph for your organization. Terms within this layer are organized by namespaces, enabling federated modeling where different domains or teams can maintain their own vocabularies while ensuring consistency and avoiding naming conflicts. Namespaces provide a mechanism for scoping concepts, attributes, and predicates, allowing organizations to model complex, distributed knowledge structures while maintaining semantic clarity and interoperability across different business domains.

Data Catalog: Technical Metadata and Schemas

The Data Catalog layer represents the classic metadata management component, focusing on technical metadata and data schemas. This layer provides a comprehensive view of your data assets through a structured hierarchy of Systems, Entities, and Fields. It serves as the central repository for cataloging structured, semi-structured, and unstructured data from various sources, including databases, documents, dashboards, reports, and machine learning models. The Data Catalog enables you to understand the technical structure of your data assets, manage relationships through constraints and foreign keys, and maintain a complete inventory of your organization’s data resources.

Data Product Catalog: Integration with DataOps, Policies, and Marketplace

The Data Product Catalog extends beyond traditional metadata management by integrating with DataOps practices, computational policies, and the marketplace. This layer manages data products as first-class citizens, supporting the entire data product lifecycle from creation to consumption. It integrates seamlessly with DataOps platforms to enable automated deployment, versioning, and lifecycle management. Computational policies are enforced throughout the data product lifecycle, ensuring compliance and governance at every stage. The marketplace integration facilitates data product discovery, access management, and consumption tracking, transforming how data assets are shared and utilized across your organization.

Navigating the Guides

Our tutorials cover a diverse range of topics, from the fundamentals of metadata creation to advanced techniques for establishing semantic relationships and enforcing data quality standards. Whether you are a beginner seeking a foundational understanding or an experienced user looking to optimize your metadata processes, you’ll find relevant guidance here.

Explore the tutorials and user guides tailored to your needs. Gain proficiency in defining business glossary terms, linking catalog assets, automating metadata extraction, and much more. Each guide is designed to empower you with the skills necessary to quickly understand how Blindata works.

• Business Glossary:

  • Master the tools for defining and managing business entities, concepts, and terms with precision.

  • Explore Concepts to categorize and organize business entities, fostering a structured metadata approach.

  • Define terms with specific attributes, such as format, naming convention, and computational rules.

  • Build logical relations between concepts, enhancing the understanding of interdependencies.

• Data Catalog:

  • Efficiently manage data catalog assets, including Systems, Entities, and Fields.

  • Learn to link catalog assets to Business Glossary terms manually, via spreadsheet upload, or through automated data classification.

  • Explore the configurations of Automated Metadata Crawling for systematic extraction of metadata from source systems.

  • Dive into the management of Constraints, Foreign Keys, and ER diagrams for enhanced data governance.

  • Understand the details of Routines, Scripts, and Stored Procedures, both imported and defined manually.

• Data Products:

  • Explore tutorials that focus on the creation, management, and optimization of data products aligned with your data ops activities.