Changes

The initial step to collecting data is to identify what information needs to be gathered and the source of data. For example, in creating a centralized system for a patient database at a hospital, once the user requirements are identified, the process of how data is collected should be considered. There are several ways of collecting data, such as interviews, surveys/ questionnaires, workshops, and observing consumers. The goal is to gather these requirements and prioritize them. Questions for surveys or interviews must be consistent to keep the data organized and easier to prioritize. The data itself should be reusable and easily transportable to another system to save time and money.

The initial step to collecting data is to identify what information needs to be gathered and the source of data. For example, in creating a centralized system for a patient database at a hospital, once the user requirements are identified, the process of how data is collected should be considered. There are several ways of collecting data, such as interviews, surveys/ questionnaires, workshops, and observing consumers. The goal is to gather these requirements and prioritize them. Questions for surveys or interviews must be consistent to keep the data organized and easier to prioritize. The data itself should be reusable and easily transportable to another system to save time and money.

* assess data requirements‑based program objectives, as well users, business and stakeholder needs

* assess program objectives based on data requirements, as well as users, business and stakeholder needs

   <b>How to achieve:</b>

   <b>How to achieve:</b>

     * Summarize how the architecture meets the data needs of the users and other key stakeholders including:

     * Summarize how the architecture meets the data needs of the users and other key stakeholders including:

         * How does the data asset contribute to outcomes/needs of the user and other stakeholders

         * How does the data asset contribute to outcomes/needs of the user and other stakeholders

         * Gaps in the existing data assets to meet the needs of the users and other stakeholders and how the architecture addresses these gaps

         * Gaps in the existing data assets to meet the needs of the users and other stakeholders and how the architecture addresses these gaps

         * Gaps in data collection and analysis and how the architecture is addressing it so that department can ensure that we are serving the members of our society  

         * Gaps in data collection and analysis and how the architecture is addressing it so that department can ensure that we are serving the members of our society  

         * Alignment to the data foundation of the departmental information/data architecture practice

         * Alignment to the data foundation of the departmental information/data architecture practice

         * Alignment to the theoretical foundation of the departmental information/data architecture practice

         * Alignment to the theoretical foundation of the departmental information/data architecture practice

           * Supporting Performance Information Profiles (PIPs) used to assess a progress towards target and broader objectives

           * Supporting Performance Information Profiles (PIPs) used to assess a progress towards target and broader objectives

   <b>Tools:</b>

   <b>Tools:</b>

     * Value Stream (Value Item and Value Proposition – Context on What we measure)

     * Value Stream (Value Item and Value Proposition – Context on what we measure)

     * KPI  Linked to benefits outcomes and objectives

     * KPI  (Linked to benefits, outcomes and objectives)

* reuse existing data assets where permissible and only acquire new data if required

* reuse existing data assets where permissible and only acquire new data if required

     <b>How to achieve:</b>

     <b>How to achieve:</b>

     * Summarize reusability of the architecture’s data assets given:

     * Summarize reusability of the architecture’s data assets given:

         * Context of data assets and user and stakeholder needs

         * Context of data assets and user and stakeholder needs

         * Data quality and fit for purpose

         * Data quality and fit for purpose

         * Privacy and Security Regulatory Framework

         * Privacy and Security Regulatory Framework

     <b>Tools:</b>  

     <b>Tools:</b>  

     * Legislative / Regulations

     * Legislative / Regulations

     <b>How to achieve:</b>

     <b>How to achieve:</b>

     * Summarize how the architecture meets the data quality requirements of third-party sources:

     * Summarize how the architecture meets the data quality requirements of third-party sources:

         * Data quality meets fit for purpose

         * Data quality meets fit for purpose

         * Data quality dimensions including:

         * Data quality dimensions including:

               * Relevance,

               * Relevance,

=== Manage and reuse data strategically and responsibly ===

=== Manage and reuse data strategically and responsibly ===

Data architecture defines the management of data by translating the business requirements into technical requirements for an organization. The management of data refers to the collection, storage, and usage of data in an information system. Furthermore, data management and the direction of its flow are guided by various framework of models, policies, rules, and standards used by the organization. They both provide a foundation to work efficiently with data as well as to govern data access by establishing roles, responsibilities and accountabilities. For example, an organization may have a system that they have conceptualized to store information. To ensure that the system succeeds in doing so, it must satisfy adequate data storage capabilities as well as role-based access functionalities. To assess said capabilities, an organization should review the system’s functions and compare them to the user/stakeholder requirements to ensure adequate support to organizational policies. The system must also ensure data lineage is maintained to be able to trace back data to its origin.

Data architecture is defined as the management of data by translating the business requirements into technical requirements for an organization. The management of data refers to the collection, storage, and usage of data in an information system. Furthermore, data management and the direction of its flow are guided by various framework of models, policies, rules, and standards used by the organization. They both provide a foundation to work efficiently with data as well as to govern data access by establishing roles, responsibilities and accountabilities. For example, an organization may have a system that they have conceptualized to store information. To ensure that the system succeeds in doing so, it must satisfy adequate data storage capabilities as well as role-based access functionalities. To assess said capabilities, an organization should review the system’s functions and compare them to the user/stakeholder requirements to ensure adequate support to organizational policies. The system must also ensure data lineage is maintained to be able to trace back data to its origin.

Data architectures define and set data standards and principles. To accomplish the process of translating business requirements into technical requirements, some duties may entail creating blueprints for data flow and data management as well as assessing potential data sources. Plans may be devised to make these sources accessible to all employees and keep them protected according to existing security and privacy policies. Data architecture identifies [data] consumers within an organization, then align with their varying requirements and allow them access at any moment with a synchronous process to deliver usable data. For example, within a hospital, nurses and doctors utilize and work with patient data. Depending on who it is, some may be required to update data such as illness or prescribed medicine, and some should view and direct based on the data, to coordinate rooms and available medical machines. It is a necessity to have a centralized system, or systems that are interoperable, with varying features and permissions to be able to access all this information at any given time. Otherwise, if non-interoperable multiple systems for different data sets were used, it would be difficult to maintain the flow of data throughout the hospital, which would cause loss opportunities of time-sensitive action that can harm patients in critical conditions.

Data architectures define and set data standards and principles. To accomplish the process of translating business requirements into technical requirements, some duties may entail creating blueprints for data flow and data management as well as assessing potential data sources. Plans may be devised to make these sources accessible to all employees and keep them protected according to existing security and privacy policies. Data architecture identifies [data] consumers within an organization, then align with their varying requirements and allow them access at any moment with a synchronous process to deliver usable data. For example, within a hospital, nurses and doctors utilize and work with patient data. Depending on who it is, some may be required to update data such as illness or prescribed medicine, and some should view and direct based on the data, to coordinate rooms and available medical machines. It is a necessity to have a centralized system, or systems that are interoperable, with varying features and permissions to be able to access all this information at any given time. Otherwise, if non-interoperable multiple systems for different data sets were used, it would be difficult to maintain the flow of data throughout the hospital, which would cause loss opportunities of time-sensitive action that can harm patients in critical conditions.

* 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>

   <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:

     * 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 steward responsibilities;

         * Identifies the data consumer responsibilities, and;

         * Identifies the data consumer responsibilities, and;

   <b>Tools:</b>

   <b>Tools:</b>

     * Target state (solution data elements)

     * Target state (solution data elements)

     * Data Foundation – Implement (Leverage the standard definition)

     * Data Foundation – Implement (Leverage the standard definition)

       * Data Catalogue

       * Data Catalogue

       * Benefits Knowledge hub

       * Benefits Knowledge hub