The global skills and competency framework for the digital world

Data management DATM

(modified)

Developing and implementing plans, policies, and practices that control, protect and optimise the value and governance of data assets.

SFIA 9 is in development

  • SFIA 9 beta due in early July 2024
  • SFIA 9 planned for publication October 2024

This is a prototype for SFIA 9. It is subject to change before publication.

Guidance notes

(modified)

Activities may include — but are not limited to:

  • developing and enforcing data governance policies to ensure data quality, compliance, and ethical usage
  • developing plans, policies and practices related to areas including, but not limited to, classification, storage, security, quality, sharing, availability, retrieval, retention and publishing
  • managing data in all its forms, ensuring alignment with business objectives and regulatory requirements
  • analysing information structures, including logical analysis of taxonomies, ontologies, data, metadata, and industry reference data
  • ensuring data is appropriately stored and archived, in line with relevant legislation
  • implementing data management practices for cloud-based services
  • applying ethical principles when handling data.
  • developing innovative ways to manage data assets
  • integrating data from multiple sources to support data pipelines and enable additional operations on the data.
       

Levels

Defined at these levels: 2 3 4 5 6

Data management: Level 1

Data management: Level 2

(new)

Assists in implementing data management activities under close guidance and supervision.

Helps create and maintain documentation of data management activities.

Helps identify and report issues and discrepancies.

Data management: Level 3

(new)

Implements standard data management practices based on detailed requirements.

Monitors and maintains data quality through regular reviews and validation checks.

Communicates the details of data management procedures to others, helping their understanding and compliance.

Data management: Level 4

(modified)

Devises and implements data governance and master data management processes for specific subsets of data.

Assesses the integrity of data from multiple sources.

Advises on data transformation of data between formats or media. Maintains and implements data handling procedures.

Enables data availability, integrity and searchability through formal data and metadata structures and protection measures.

Data management: Level 5

(modified)

Devises and implements data governance and master data management processes.

Derives data management structures and metadata to support consistent data retrieval, combination, analysis, pattern recognition, and interpretation across the organisation.

Independently validates external information from multiple sources. Plans effective data storage, sharing, and publishing practices within the organisation.

Identifies and addresses issues preventing optimal use information assets. Provides expert advice to maximise data asset value, ensuring data quality and compliance.

Data management: Level 6

(modified)

Leads the strategic direction for data management and governance, establishing policies and frameworks that align with business and regulatory requirements. Derives an overall strategy of master data management that supports the development and secure operation of data and digital services.

Creates organisational policies, standards, and guidelines for data management, ensuring ethical principles are applied.

Plans, establishes and manages processes for regular and consistent access to external data sources, ensuring their validation and integration.

Data management: Level 7