Parent Framework: COBIT 2019
Domain: Align Plan and Organise
Managed Data
Achieve and sustain effective management of the enterprise data assets across the data life cycle, from creation through delivery, maintenance and archiving.
Purpose
Ensure effective utilization of the critical data assets to achieve enterprise goals and objectives.
Management practices
APO14.01 Define and communicate the organization’s data
Define how to manage and improve the organization’s data assets, in line with enterprise strategy and objectives. Communicate the data management strategy to all stakeholders. Assign roles and responsibilities to ensure that corporate data are managed as critical assets and the data management strategy is implemented and maintained in an effective and sustainable manner.
APO14.02 Define and maintain a consistent business glossary.
Create, approve, update and promote consistent business terms and definitions to foster shared data usage across the organization.
APO14.03 Establish the processes and infrastructure for metadata
Establish the processes and infrastructure for specifying and extending metadata about the organization’s data assets, fostering and supporting data sharing, ensuring compliant use of data, improving responsiveness to business changes and reducing data-related risk
APO14.04 Define a data quality strategy.
Define an integrated, organization wide strategy to achieve and maintain the level of data quality (such as complexity, integrity, accuracy, completeness, validity, traceability and timeliness) required to support the business goals and objectives.
APO14.05 Establish data profiling methodologies, processes and tools.
Implement standardized data profiling methodologies, processes, practices, tools and templates that can be applied across multiple data repositories and data stores.
APO14.06 Ensure a data quality assessment approach.
Provide a systematic approach to measure and evaluate data quality according to processes and techniques, and against data quality rules.
APO14.07 Define the data cleansing approach.
Define the mechanisms, rules, processes, and methods to validate and correct data according to predefined business rules.
APO14.08 Manage the life cycle of data assets.
Ensure that the organization understands, maps, inventories and controls its data flows through business processes over the data life cycle, from
APO14.09 Support data archiving and retention.
Ensure that data maintenance satisfies organizational and regulatory requirements for availability of historical data. Ensure that legal and regulatory requirements for data archiving and retention are met.
APO14.10 Manage data backup and restore arrangements.
Manage availability of critical data to ensure operational continuity.
Skills
Data management DATM
The management of practices and processes to ensure the security, quality, integrity, safety and availability of all forms of data and data structures that make up the organisation’s information. The management of data and information in all its forms and the analysis of information structure (including logical analysis of taxonomies, data and metadata). The development of innovative ways of managing the information assets of the organisation.
Data modelling and design DTAN
The development of models to represent and communicate data requirements and to enable organisations to understand their data assets and the relationships between real-world entities. The investigation, analysis and scoping of data requirements to support the development of software systems, data integration and data retrieval activities. The iteration, review and maintenance of data requirements and data models.
Information assurance INAS
The protection of integrity, availability, authenticity, non-repudiation and confidentiality of information and data in storage and in transit. The management of risk in a pragmatic and cost effective manner to ensure stakeholder confidence.
Information governance IRMG
The overall governance of how all types of information, structured and unstructured, whether produced internally or externally, are used to support decision-making, business processes and digital services. Encompasses development and promotion of the strategy and policies covering the design of information structures and taxonomies, the setting of policies for the sourcing and maintenance of the data content, and the development of policies, procedures, working practices and training to promote compliance with legislation regulating all aspects of holding, use and disclosure of data.
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