Blog by

Stella Kahianyu, Data Governance Analyst

South-End Tech Limited, Nairobi Kenya.

November 22^nd, 2024.

Introduction

In an increasingly digital world, data is one of the most valuable assets companies possess. With inappropriate governance, it becomes a liability. A strong data governance framework ensures data is managed, accessible, reliable and secure. This blog will explore actionable steps to build a data governance framework aligning with your business goals.

Step 1: Define Your Data Governance Goals

The first step involves outlining data governance goals clearly based on the industry. Some common goals to consider include:

1. Data Quality: Ensuring data is accurate, consistent, and reliable.
2. Regulatory Compliance: Adhering to relevant legal requirements, such as Data Protection Act (2019), GDPR, or HIPAA.
3. Operational Efficiency: Streamlining data management processes to reduce time spent on data issues.
4. Enhanced Security and Privacy: Protecting sensitive data from unauthorized access or breaches.

Having clear goals will guide the framework’s design and help gain support from stakeholders.

Step 2: Establish Roles and Responsibilities

Data governance is not a one-person job. A successful framework relies on defining specific roles and responsibilities to manage data effectively:

1. Data Owners: Are responsible for certain datasets. They define access rights, quality standards, and compliance requirements.
2. Data Stewards: Stewards oversee data governance operations, maintaining data quality and supporting data owners in implementing governance policies.
3. Data Governance Committee: Across-functional team that includes representatives from IT, legal, compliance, and business units. The committee drives data governance strategy, reviews progress, and makes key decisions.

Step 3: Create Data Policies and Standards

Data governance requires clear, enforceable policies, defining how data is collected, stored, accessed, and maintained. Consider establishing policies in these key aspects:

1. Data Quality Standards: Set benchmarks for accuracy, completeness, and consistency.
2. Data Classification: Classify data on sensitivity and importance basis i.e., public, confidential, or restricted.
3. Data Access Policies: Define who can access what data and under what conditions. Use role-based access controls to limit exposure to sensitive data.

Developing policies and standards ensures that all employees know the rules and their responsibilities when handling data.

Step 4: Develop a Data Governance Culture

Even the best framework won’t work if people don’t adhere to it. Building a data governance culture is about fostering a shared commitment to data integrity and responsibility. Here’s how to encourage this mind set:

1. Provide Training: The importance of data quality, security and compliance are key aspects of data governance policies to train employees on.
2. Encourage Accountability: To instil accountability, data governance should be part of employees’ roles and responsibilities.
3. Lead by Example: The management endorsing proper data governance policies, reinforces their importance to the organization.

Step 5: Monitor, Audit, and Improve

Data governance is an ongoing process requiring regular monitoring and updates. Schedule routine audits to check data compliance, accuracy, and adherence to policies. This will help you identify issues early and improve the framework as new challenges or opportunities arise. Key metrics to monitor include:

1. Data Quality Scores: Track metrics like data completeness, consistency, and accuracy over time.
2. Compliance Rate: Measure how well your organization is following governance policies.
3. Access Control Compliance:  Check that access to sensitive data aligns with your access policies.

Use feedback from audits to update policies, standards, and tools, keeping your data governance framework aligned with evolving business needs and regulatory requirements.

Conclusion

Building a strong data governance framework is essential for managing data effectively, reducing risks, and gaining business insights. From defining goals and roles to fostering a data governance culture, each step contributes to a comprehensive framework aligning with data practices with organizational needs. Keep in mind, data governance is a journey, start with achievable goals, monitor progress, and continuously adapt. With a solid data governance framework, your organization will be well-positioned to unlock the full potential of its data assets.

Final Takeaway

Data governance doesn’t have to be complicated. Start with the basics, involve key stakeholders, and build gradually. Overtime, a good data governance framework will lead to better decision-making, improved compliance, and a more data-driven organizational culture.

Please do not hesitate to contact us for your Data Governance Solutions and Cybersecurity Service needs.

Tel: +254115867309| +254721864169| +254740196519 or

Email: skahianyu@southendtech.co.ke ;info@southendtech.co.ke; dataprotection@southendtech.co.ke