DNA-102: Enterprise Data Management

• Data management structures
• Information handling approaches
• Data management standards and tools
• Typical protocols in information asset management
• Internal and external information management guidelines and rules
• Define data management structures to align and streamline processes of data ownership, retrieval, combination and usage
• Plan processes for effective data storage, sharing and utilisation within the organisation
• Update policy, standards and procedures on data management for compliance with relevant legislation
• Introduce relevant standards and tools that can be applied to the management and treatment of critical data
• Identify gaps, inefficiencies and potential risks in existing data management processes
• Propose enhancements or modifications to data handling procedures
• Establish internal processes to monitor compliance of information or data handling and access requests with approved procedures
• Provide ongoing advice to ensure proper adoption of and adherence to data policies and information architecture

MODULE 1: DATA GOVERNANCE AND MANAGEMENT
Topics:

• Data management approaches and frameworks
• Internal and external information regulation policies and requirements
• Establishing the organisation’s data management office

Mapped to:

• K1 Data management structures
• A1 Define data management structures to align and streamline processes of data ownership, retrieval, combination and usage
• A4 Introduce relevant standards and tools that can be applied to the management and treatment of critical data

Rationale for Sequencing of the Units

• The first learning unit gives the learner an overview of data strategy, to leverage data to make better business decisions through data management and usage while adhering to data governance regulations and policies.
• Learners are taught data management approaches and frameworks for data architecture, data storage, data operations.

MODULE 2: DATA STORAGE, SHARING, UTILISATION, HANDLING AND MANAGEMENT
Topics:

• Capturing, retention and utilisation of critical data
• Guidelines for effective storage, sharing and publishing within the organization
• Corporate Standard Operating Procedures (SOP), protocols and standards for data management, sourcing, handling and treatment
• Pre-mortem analysis on existing data management practice.

Mapped to:

• K2 Information handling approaches
• K5 Internal and external information management guidelines and rules
• A2 Plan processes for effective data storage, sharing and utilisation within the organisation
• A5 Identify gaps, inefficiencies and potential risks in existing data management processes
• A6 Propose enhancements or modifications to data handling procedures

Rationale for Sequencing of the Units

• Subsequently, the next learning unit, learners are taught the data lifecycle and information handling.
• Learners begin to look at developing a data strategy.
• Learners are taught information handling approaches and data management guidelines.
• Learners are taught how to plan processes to ensure data stays reliable, have SOP and protocols for data management, data security and data privacy.
• Learners are taught how to analyse existing data management processes to identify gaps, inefficiencies and potential risks as well as propose enhancements to data handling procedures to mitigate the issues identified.

MODULE 3: COMPLIANCE AND ADVISORY
Topics:

• Monitor adoption and adherence to data policies and information architectures
• Advisory support to overall data management process and standards to ensure greater adoption and with risk balancing

Mapped to:

• K3 Data management standards and tools
• K4 Typical protocols in information asset management
• A7 Establish internal processes to monitor compliance of information or data handling and access requests with approved procedures
• A8 Provide ongoing advice to ensure proper adoption of and adherence to data policies and information architectures

Rationale for Sequencing of the Units

• In this final learning unit, learners are taught how to execute data strategy in the organisation through establishing internal processes to monitor adoption and compliance.
• Learners are also taught how to provide advisory support to ensure proper adoption of and adherence to data policies and information architectures with a risk balancing approach.