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Data Dictionary Template
What is Data Dictionary Template?
A Data Dictionary Template is a structured framework that serves as a comprehensive repository for metadata about the data elements within an organization’s data architecture. It provides standardized definitions, data types, relationships, and attributes for each data element, facilitating consistent understanding and use across various stakeholders, including business analysts, developers, and data governance teams. Employing best practices from frameworks like TOGAF, the Data Dictionary Template aids in establishing a common language around data, ensuring alignment with enterprise architecture principles and promoting effective data management, quality assurance, and compliance with regulatory standards. It is essential for enhancing data interoperability and supports informed decision-making by providing clarity on data assets across the enterprise.
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AI Prompt: Data Dictionary Template
Imagine you're an [Application Lifecycle Management (ALM)] advocate striving to streamline communications between business stakeholders and technical teams. Your task is to design a comprehensive [Data Dictionary Template] that can enhance understanding and utilization of data across the organization. This template should include key components such as [Field Name, Data Type, Description, Constraints, and Sources], ensuring that everyone speaks the same data language. For inspiration, consider examples from high-performing organizations that effectively manage their data assets and foster collaboration. As you draft your template, think about adapting it to different departments—allowing flexibility while maintaining essential details, ensuring clarity for both technical and non-technical users. The final output should be an easy-to-use, visually appealing, and standardized document that aligns with enterprise architecture best practices, ultimately driving better data governance, quality, and utilization across your projects.
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Data Dictionary Template
1. Table of Contents
2. Introduction
This Data Dictionary provides a comprehensive overview of data elements used within the Enterprise Architecture. It includes definitions, types, constraints, and relationships between different data elements.
3. Data Element Definitions
| Data Element Name | Description | Data Type | Constraints | Default Value | Example Values |
|---|---|---|---|---|---|
Element Name 1 | Brief description of the data element. | String/Integer/Date | Required/Optional, Length, etc. | Default Value | Sample data |
Element Name 2 | Brief description of the data element. | String/Integer/Date | Required/Optional, Length, etc. | Default Value | Sample data |
Element Name 3 | Brief description of the data element. | String/Integer/Date | Required/Optional, Length, etc. | Default Value | Sample data |
4. Data Relationships
| Source Data Element | Target Data Element | Relationship Type | Description |
|---|---|---|---|
Source Element 1 | Target Element 1 | One-to-One/One-to-Many | Brief description of the relationship. |
Source Element 2 | Target Element 2 | One-to-One/One-to-Many | Brief description of the relationship. |
5. Data Governance
- Data Steward: Name of the person responsible for this data element.
- Data Owner: Name of the entity that owns the data.
- Retention Policy: Guidelines for data retention and deletion.
6. References
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