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GC Enterprise Architecture/Framework (view source)
Revision as of 17:03, 19 February 2021
, 17:03, 19 February 2021no edit summary
* Usability
* Usability
* Data quality mechanism
* Data quality mechanism
<b>Tools:</b>
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
* Data Science and Machine Platform
=== Manage and reuse data strategically and responsibly ===
=== Manage and reuse data strategically and responsibly ===
* define and establish clear roles, responsibilities, and accountabilities for data management
* define and establish clear roles, responsibilities, and accountabilities for data management
<b>How to achieve:</b>
* Summarize how the architecture assists in defining key data management roles and their responsibilities to ensure data is correct, consistent, and complete including:
* Identifies the data steward responsibilities;
* Identifies the data consumer responsibilities, and;
* Identifies the data custodian responsibilities.
<b>Tools:</b>
* Stakeholders
* Business Process Model
* Functional Requirements
* Business Glossary
* identify and document the lineage of data assets
* identify and document the lineage of data assets
<b>How to achieve:</b>
* Summarize how the architecture’s data assets demonstrate alignment with department's data governance and strategy including:
* Alignment to the data foundation of the ESDC information/data architecture practice
* Alignment to the theoretical foundation of the ESDC information/data architecture practice
<b>Tools:</b>
* Target state (solution data elements)
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
* Data Science and Machine Platform
* Theoretical Foundation
* EDRM (Conceptual and Logical)
* Business Glossary
* Departmental Data Strategy
* define retention and disposition schedules in accordance with business value as well as applicable privacy and security policy and legislation
* define retention and disposition schedules in accordance with business value as well as applicable privacy and security policy and legislation
<b>How to achieve:</b>
* Summarize for each key data assets:
* Retention and disposition schedules
* Disposition process
<b>Tools:</b>
* Target state (solution data elements)
* Non Functional Requirements
* IM Best Practices and Standards
* ensure data are managed to enable interoperability, reuse and sharing to the greatest extent possible within and across departments in government to avoid duplication and maximize utility, while respecting security and privacy requirements
* ensure data are managed to enable interoperability, reuse and sharing to the greatest extent possible within and across departments in government to avoid duplication and maximize utility, while respecting security and privacy requirements
<b>How to achieve:</b>
* Summarize how the architecture enables interoperability, reuse and sharing to the greatest extent possible within and across departments
* Summarize how the architecture avoids data duplication
<b>Tools:</b>
* Target State
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Benefits Knowledge hub
* Data Lake (growth)
* contribute to and align with enterprise and international data taxonomy and classification structures to manage, store, search and retrieve data
* contribute to and align with enterprise and international data taxonomy and classification structures to manage, store, search and retrieve data
<b>How to achieve:</b>
* Summarize the alignment to departmental/GC:
* Data taxonomy structure
* Data classification structure
<b>Tools:</b>
* Data Foundation – Implement (Leverage the standard definition)
* Data Catalogue
* Theoretical Foundation
* EDRM (Conceptual and Logical)
* Business Glossary
=== Use and share data openly in an ethical and secure manner ===
=== Use and share data openly in an ethical and secure manner ===
