Data Inventory & Catalog¶
Overview¶
A Data Inventory is a comprehensive listing of all enterprise data assets, while a Data Catalog provides a structured, searchable repository with metadata, lineage, and classification.
Together, they enable visibility, accountability, and governance for Nissan North America’s (NNA) critical data assets.
This section outlines the process, structure, and best practices for creating and maintaining a data inventory and catalog.
Purpose¶
- Maintain a centralized record of all data assets across domains.
- Support data governance, quality, compliance, and analytics initiatives.
- Enable data discovery, lineage tracking, and impact analysis.
- Provide a foundation for stewardship, classification, and lifecycle management.
Key Components of Data Inventory¶
| Component | Description |
|---|---|
| Data Asset Name | Unique identifier for the dataset, table, or system. |
| Domain | Business domain (e.g., Customer, Vehicle, Dealer, Product). |
| Owner | Assigned Data Owner responsible for quality, access, and usage. |
| Steward | Data Steward responsible for day-to-day governance and monitoring. |
| Source System | Origin of the data (ERP, CRM, legacy system, external feed). |
| Classification | Public, Internal, Confidential, Sensitive/Restricted. |
| Retention Policy | Rules for archival and deletion. |
| Usage | Business purpose or downstream applications. |
| Quality Metrics | Data accuracy, completeness, timeliness, and other KPIs. |
| Lineage | Upstream and downstream systems consuming or producing the data. |
| Last Updated | Date of last update or review of the asset. |
Data Catalog Features¶
A data catalog extends the inventory with metadata, discovery, and governance functionality:
- Search & Discovery: Easily locate datasets by name, domain, or keyword.
- Metadata Management: Store definitions, classifications, quality metrics, lineage, and ownership.
- Lineage Visualization: Understand data flow and dependencies across systems.
- Stewardship & Accountability: Track owners, stewards, and change history.
- Usage Analytics: Monitor frequency of access, queries, and reports.
Inventory & Catalog Process¶
- Identify Data Assets: Compile a comprehensive list of structured and unstructured data sources.
- Capture Metadata: Document data definitions, owners, classification, source systems, and quality metrics.
- Validate & Classify: Ensure each data asset is assigned a classification level and steward/owner.
- Populate Catalog: Enter metadata and inventory into a centralized tool or repository.
- Maintain & Update: Regularly review assets, update ownership, lineage, and quality metrics.
- Integrate with Governance: Connect inventory and catalog to policies, data quality rules, and compliance requirements.
Roles & Responsibilities¶
| Role | Responsibilities |
|---|---|
| Data Owner | Approves catalog entries, ensures accuracy, maintains accountability. |
| Data Steward | Maintains metadata, monitors data quality, and updates lineage. |
| IT / Data Engineering | Implements catalog tools, automates metadata capture, supports integration. |
| Data Consumer | Uses catalog to locate, understand, and request data assets. |
Tools & Technologies¶
- Metadata management platforms (e.g., Collibra, Alation, Informatica EDC)
- Data cataloging tools integrated with enterprise systems
- Automated scripts for lineage and quality metric capture
- Reporting and visualization for asset usage and compliance
Visual Representation¶
flowchart TB
A[Data Sources] --> B[Data Inventory]
B --> C[Data Catalog]
C --> D[Metadata & Lineage]
C --> E[Ownership & Stewardship]
C --> F[Classification & Quality Metrics]
D --> G[Data Discovery & Analytics]