Roles and Oversight in Data Management
In today's data-driven world, establishing a robust data governance framework is crucial for businesses to ensure data quality, regulatory compliance, and alignment with business objectives. Here's a comprehensive guide to defining and assigning data governance roles and responsibilities, based on expert recommendations.
Identifying Key Roles
A robust data governance framework typically includes several key roles:
- Data Owners: These individuals are responsible for defining access, usage, and lifecycle decisions for specific data sets.
- Data Stewards: They oversee day-to-day data management, enforce standards, and help resolve issues.
- Data Governance Council: This group provides strategic leadership and oversight, including policy development and compliance.
- IT and Security Teams: They implement and enforce data security controls and compliance checks.
- Business Users: They contribute to data and require guidance on governance policies.
Defining Responsibilities Clearly
Each role should have well-documented responsibilities that align with organizational goals and regulatory requirements. This includes ensuring data quality and integrity, maintaining data security and privacy, enforcing data governance policies, and making strategic decisions about data management.
Establishing Accountability
Assign clear ownership and accountability for data across departments and functions. This ensures that there is no ambiguity in resolving data-related issues or enforcing policies.
Developing Comprehensive Policies
Create policies that cover data classification, quality standards, security requirements, and compliance obligations. Ensure these policies are regularly reviewed and updated to reflect changes in legal, operational, and technological landscapes.
Implementing Governance Framework
Structure the governance framework around the four pillars of data governance:
- People: Clear roles and responsibilities
- Process: Defined procedures for data management
- Technology: Tools and systems to support governance
- Policy: Guidelines and standards for data use and management
Operational Responsibilities
Operational responsibilities, as described by Bob Seiner, include ensuring good data definitions and values, following the rules to identify and classify data access, identifying and documenting regulatory issues with the data, exchanging knowledge with colleagues and managers, and communicating new/changed business requirements to the business units impacted and concerns to those at the tactical levels.
Data Governance SME Functions
The Data Governance SME functions, as described by Johnson, involve applying Data Governance rules and standards to meet or exceed an acceptable threshold for Data Quality. They also include assisting others and cultivating buy-in when an enterprise embarks on new initiatives.
The Support Level
The support level, as described, consists of a few people in a Data Governance Office (DGO) or an administrator, like a CDO, who run the Data Governance program along with assistance from partners. The DGO or administrator reports results (such as Data Quality metrics or Data Governance adoption) to the strategic level.
The Operating Model of Roles and Responsibilities
Bob Seiner has created an "Operating Model of Roles and Responsibilities" to guide companies in understanding Data Governance operations. He recommends taking people who demonstrate existing activities governing data and acknowledging their contribution to Data Governance formally. The support level is considered critical to getting Data Governance done, as a program team will eventually emerge to determine how to build Data Governance.
Adopting the Mindset that "Everyone is a Data Steward"
Bob Seiner, president and principal of KIK Consulting and Educational Services, suggests adopting the mindset that "everyone is a data steward." By initially activating existing roles instead of assigning them, enterprises have an edge in influencing acceptance among workers.
The Importance of Data Governance
According to a our platform® Trends in Data Management(TDM) survey, 81.89% of participants have either implemented a Data Governance program or plan to initiate one as of 2022. However, 54.63% of those surveyed listed a lack of Data Governance as a major Data Management challenge.
By defining and assigning data governance roles and responsibilities effectively, organizations can overcome these challenges and reap the benefits of data governance, including improved data quality, enhanced regulatory compliance, and better alignment with business objectives.
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