Oman Data Governance and Management Office Establishment Guidelines
Oman Data Governance and Management Office Establishment Guidelines
The Sultanate of Oman has established comprehensive
guidelines to assist government entities in setting up Data Governance and
Management Offices (DGMO), as part of its broader National Data Governance and
Management Regulatory Framework. These guidelines are detailed in the
"Data Governance and Management Office Establishment Guidelines"
issued by the Ministry of Transport, Communications, and Information Technology
(MTCIT).
Oman’s
strategic vision under Vision 2040 positions data as a critical national asset.
As government entities drive digital transformation, robust data governance is
essential for transparency, innovation, and economic growth.
National
Data Governance Vision and Mission
Vision: Data as a key enabler for decision-making and
leading economic development in the Sultanate of Oman
Mission: Activate an effective national data
governance framework that fosters collaboration between data owners and end
users, through setting clear directions with the required level of policies for
managing and governing data, adopting best practices, and ensuring continuous compliance,
to reposition data as a driving force for the national economy.4
National
Data Governance Framework
The National Data Governance framework outlines a structured
approach to help entities manage their data effectively. It involves defining
policies, processes, and responsibilities to ensure that data is managed in a
consistent manner throughout the data lifecycle. The framework comprises of
three components:
·
National Data Governance and Management
Policies – The policies outline the necessary requirements across 13 out of
the 14 data governance and management domains to establish a robust data
governance practice within the government entities. The Document and Content
Management domain will be covered by the existing policies/laws developed for
the sultanate.
·
Data Governance and Management Office
Establishment Guidelines – The guidelines provide the necessary elements to
support the government entities for establishing their Data Governance and
Management Office including the mandate, services and processes, organization
structure, roles, and responsibilities, positioning within the entity and
governance model.
·
National Data Governance and Management
Compliance Assessment Model -The model outlines the compliance assessment
methodology, the implementation priorities, and the assessment criteria for
enabling the government entities to comply with the national data governance
and management policies.
Key Components of the Guidelines
- Organizational
Structure and Roles: The guidelines recommend the formation of a
dedicated DGMO within each government entity. This office should have
clearly defined roles and responsibilities to oversee data governance and
management activities.
- Core
Functions: The DGMO is expected to handle various tasks, including
data quality management, metadata management, data security, and
compliance with data-related policies. It should also coordinate with
other departments to ensure effective data utilization.
- Competency
Requirements: Personnel within the DGMO should possess specific
competencies in data management, analytics, and policy implementation to
effectively carry out their duties.
- Processes
and Services: The guidelines outline standard processes for data
lifecycle management, including data collection, storage, processing, and
dissemination. They also emphasize the importance of establishing services
that support data sharing and interoperability among government entities.
- Compliance
and Assessment: To ensure adherence to national data governance
policies, the guidelines introduce a compliance assessment model. This
model provides a methodology for evaluating the effectiveness of data
governance practices within government entities.
These guidelines are part of a broader initiative to enhance
data governance in Oman, which also includes the National Data Governance and
Management Policies and a Compliance Assessment Model. Together, these
components aim to standardize data management practices across government
entities, ensuring data is treated as a strategic asset to support
decision-making and public service delivery.
Data
Governance Principles
1.
Data is a national asset Develop practices that
enable realization of the inherent value of data as a national asset to drive
innovation and unlock economic growth through data integrity, monetization,
transparency and accountability
2.
A data-driven culture is encouraged Establish
processes and develop skills required for entities to utilize their data,
derive meaningful insights and leverage technology to improve their decision
making and operational efficiency.
3.
Data is shared and is available on time Develop
practices to facilitate seamless internal and external sharing of data,
ensuring that data users obtain information in a timely manner, thereby
improving the quality and efficiency of decision-making processes.
4.
Data is trusted by all stakeholders Establish
practices for providing reliable, accurate and fit for purpose data to build
datatrust and confidence thereby, facilitating informed decision making
5.
Data is understood uniformly across all
stakeholders Establish practices that enable a uniform understanding of the
data to facilitate efficient data exchange and analysis thereby promoting
reliability and efficiency in utilizing data assets within the entity.
6.
Data practices are compliant with regulatory
requirements Develop data governance and management practices that uphold the
regulatory requirements to ensure lawful, ethical and responsible handling of
data across the business processes of the entities.
7.
Data is managed across its lifecycle as per
business needs Develop practices that help collect, store, dispose/archive data
as per its relevance and purpose along with delivering it to the data
consumers.
Data
Governance and Management (DGM) Office Value Proposition
Data Governance and Management Office plays a crucial role
in an entity by overseeing and managing the entity’s data management strategy
while ensuring alignment with its overarching vision and goals. The potential
advantages of the data governance and management office are as follows
·
Regulatory Compliance - The DGM Office ensures
accountability for developing, implementing, and ensuring adherence to the data
governance and management policies in alignment with the National Data
Governance Framework. It facilitates timely availability of reliable and
consistent data essential for regulatory reporting through standardized
processes for managing data quality and creating data catalogues, thus ensuring
regulatory compliance.
·
Strategic Decision-Making - The DGM Office
supports informed strategic decision-making by delivering precise insights,
achieved through the enhancement of data quality, availability, use cases, and
associated controls.
·
Operational Efficiency - The DGM office promotes
seamless data sharing and collaboration by providing guidelines for
establishing data stewardship and accountabilities. Additionally, reduces data
redundancies by establishing processes for business units to consolidate their
critical data into a single source of truth.
·
Stakeholder Trust - The DGM Office promotes data
transparency by facilitating implementation of standardized processes for data
classification, privacy, and personal data protection.
·
Economic growth - The DGM Office supports the
development of policies and processes that adhere to regulatory requirements
and provision of open data, advanced analytics, and data monetization which
promotes creating new revenue streams leveraging the organization’s data.
Data
Governance and Management Office Mandate
The entity shall establish a Data Governance and Management
Office to drive its Data Governance program. The Data Governance and Management
Office shall carry out the following key responsibilities:
· Develop the entity’s data
management strategy, steer its execution through development of an
implementation plan and establish key performance metrics to continuously
monitor progress of the entity’s data governance program.
·
Develop and review the entity’s data governance and management policies and
processes in accordance with its strategic business objectives and the National
Data Governance and Management policies.
·
Coordinate with the business units and supervise their data cataloguing and
data quality management implementation.
·
Support the entity to transform into a data-driven organization by extracting
insights and achieving financial returns from data.
·
Oversee methods for data sharing and storage along with open data publishing
while establishing mechanisms for citizens to request and access public data.
·
Conduct employee training sessions and awareness workshops for data governance
practices.
· Ensure compliance to the
National Data Governance and Management framework4, prepare compliance reports
and present them to the senior leadership, sector regulators (if applicable)
and MTCIT.
·
Document and maintain the issues escalated to the Data Governance Committee,
the decisions taken on them along with the approval received.
·
Represent the entity and attend relevant national and sectoral meetings and
initiatives for data governance.
The Data Governance and Management Office shall be
providing the following Data Governance services through the related processes
1.
Data Management Strategy and
Implementation Roadmap Development - This service aims to develop the data
management strategy of the entity and oversee its implementation through a
roadmap of initiatives and projects through collaboration with the entity’s
business units along with periodic monitoring.
2.
Data Governance and Management Policies
and Processes Development and Review - This service aims to develop and
enforce the policies and processes for data governance and management aligning
to the strategic objectives of the entity as well as the National Data
Governance Framework.
3.
Data Catalog Development and Management
- This service aims to supervise the development and periodic updates to the
entity’s data dictionary and business glossary.
4.
Data Classification Governance - This
service aims to supervise the entity’s methods for classifying their
information assets along with development of artifacts for maintaining the
classification information.
5.
Data Quality Governance - This
service aims to oversee the development of the framework and processes required
to manage and implement data quality activities and to ensure the periodic
monitoring of data quality levels. It also includes identifying and remediating
data quality issues.
6.
Data Architecture Governance - This
service aims to oversee and ensure that the business needs are translated into
requirements for managing the data across its lifecycle.
7.
Data Sharing Governance - This
service aims to oversee the management and handling of data sharing and sharing
agreement.
8.
Data Analytics Governance - This
service aims to oversee identification and prioritization of the analytics use
cases based on the entity’s strategic requirements across business units within
the entity.
9.
Open Data Implementation Oversight - This
service aims to support the business units to identify, finalize, and publish
open data assets for public use.
10.
Reference and Master Data Governance
- This service aims to oversee the identification and operationalization of the
reference and master data objects within the entity.
11.
Data Monetization Governance - This
service aims to oversee identification, prioritization and implementation of
the opportunities for Data Monetization based on entity’s strategic
requirements.
12.
Public Information Request Management
Oversight - This service aims to supervise the processes for managing the
citizen requests to access the entity’s public information.
13.
Personal Data Protection Governance -
This service aims to support the entity’s processes for collecting, processing,
storing, and deleting of personal data while ensuring protection of the data
subject’s rights on their personal information
14.
Data Governance Training and Awareness
- This service aims to raise the level of awareness of the entity’s employees
regarding the importance of data, and the data governance and management
practices, through awareness sessions and training workshops
15.
Data Governance and Management Policies
Compliance - This service aims to measure the entity’s compliance to the
defined data governance and management policies, prepare compliance reports and
follow up on corrective actions for cases of non-compliance as per the
‘National Data Governance and Management Compliance Assessment Model’.
DGM
Office Organization Structure
Governance
Model
A governance model shall be established for structuring the
data governance and management functions of the entity and handling its data
governance related issues. The governance model includes the following three
forums:
·
Data Governance Committee: The Data
Governance Committee sets the strategic direction for the entity’s data
governance and management program and acts as the final authority to decide on
all decisions and issues related to data governance and management. It oversees
the performance of the entity’s data governance and management office, approves
the entity’s data management strategy, policies and processes along with
obtaining sponsorship for the entity’s data governance and management program
initiatives.
o Meeting Frequency: Quarterly
·
Data Governance and Management Working Team:
The Data Governance and Management Working Team implements the data governance
and management policies and related practices through the performance of
day-to-day activities across all business units within the entity.
o Meeting Frequency: Weekly
The services performed by the Data Governance and Management
Office shall be monitored and evaluated through tracking of the operational
performance indicators that shall include, at minimum, the following:
·
Strategy and implementation roadmap
development - Initiative completion indicator - The indicator measures the
ratio of the number of initiatives completed over the number of initiatives
planned as per the implementation roadmap at program level.
·
Policies and processes development and review
- Policy control implementation indicator - The indicator measures the ratio of controls
linked to policies implemented over total control linked to policies approved
for implementation.
·
Data catalog development and management -
Data catalog development ratio indicator - This indicator measures the ratio of
the number of CDEs catalogued over the total number of CDEs identified. Data
catalog change indicator This indicator measures the ratio of the number change
requests executed for the data catalog over the total number of change requests
received.
·
Data Classification Governance - Data
Classification indicator - The indicator measures the ratio of the number of
data assets classified over the total number of data assets for a particular
entity.
·
Data Quality Governance. Data Quality
Index - This indicator measures the ratio of records that pass the DQ rules
against the total number of records processed. Data Quality issue resolution
index. The indicator measures the ratio of data quality issues resolved over
total data quality issues reported. Resolution time indicator The indicator
measures the average time taken to provide a resolution for a data quality
issue
·
Data architecture governance Data
architecture alignment indicator The number of architectural components
implemented in alignment with the developed target data architecture.
·
Data sharing governance. Data sharing
agreement adoption indicator. The indicator measures the number of data sharing
requests executed through the data sharing agreements over total number of data
sharing requests executed.
·
Data analytics business use case
implementation. Analytics business use case implementation indicator. The
indicator measures the total number of potential data analytics business use
cases implemented over the total number of business use cases identified
·
Data analytics business use case
implementation - Analytics business use case implementation indicator - The
indicator measures the total number of potential data analytics business use
cases implemented over the total number of business use cases identified
·
Reference and master data governance - Master
Data Implementation Indicator - The indicator measures the number of master
data objects implemented in the MDM tool over the number of master data objects
planned for implementation.
·
Data monetization governance - Data
Monetization implementation indicator - The indicator measures the number of
opportunities implemented for revenue generation or cost optimization over the
number of opportunities identified for revenue generation or cost optimization.
·
Public information request management
oversight - Public information request execution time indicator - The
indicator measures the average time taken to process and execute the requests
for access to entity’s public information submitted by individuals
·
Personal Data Protection governance - Personal
data identification indicator - The indicator measures the number of business
processes reviewed for personal data identifications over the total number of
business processes within the entity
·
Data governance training and awareness - Training
completion index - The indicator measures the ratio of the count of training
and awareness sessions held by an entity over total count of training and
awareness sessions planned.
·
Data Governance and Management policies
compliance - Non-compliance indicator - The indicator measures the number
of cases of non-compliance observed during the internal compliance assessment
with respect to National Data Governance and Management Policies.
·
Data Governance and Management process
automation - Process automation indicator - The indicator measures the
ratio of number of data governance and management processes automated (through
adoption of data governance tool) over the total number of data governance and
management processes.
For a detailed understanding, you can access the full
guidelines here
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