Implementing Data Governance Policies for Regulatory Compliance

How does a data governance policy help your organization? And why do you need it?

Today, organizations are grappling with an ever-increasing volume of data and the need to ensure compliance with various regulations. Failure to comply with these regulations can result in severe penalties, reputational damage, and loss of customer trust. This is where data governance policies come into play, serving as a crucial component of an organization’s overall data management strategy.

What are Data Governance Policies?

Data governance policies are a set of rules, guidelines, and procedures that define how an organization manages its data assets. These policies establish standards and best practices for various aspects of data management service, including data quality, security, privacy, access, usage, retention, and disposal.

The primary objectives of data governance policies are to:

• Ensure regulatory compliance: Comply with data privacy, security, and retention laws/standards.
• Maintain data quality: Define standards for accurate, complete, consistent, and timely data.
• Protect sensitive data: Identify, classify, and secure sensitive data against breaches/unauthorized access.
• Facilitate data access and sharing: Guidelines for controlled, accountable data access and sharing.
• Ensure data retention and archiving: Govern data retention periods and archiving/disposal procedures.
• Promote data governance and stewardship: Assign data ownership, and stewardship roles for accountability.

These policies serve as the guiding framework for utilizing data governance tools, which facilitate the implementation and enforcement of these policies across the organization’s data management processes.

Types of Data Governance Policies

Data governance policies encompass a wide range of areas, each designed to address specific regulatory requirements and organizational needs. Some common types of data governance policies include:

• Data Privacy and Security Policies: These policies outline the measures and procedures for protecting sensitive data, such as personal information, financial records, and intellectual property. They ensure compliance with regulations like the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Health Insurance Portability and Accountability Act (HIPAA).
• Data Quality Policies: Data quality is essential for making informed decisions and ensuring regulatory compliance. These policies establish standards and processes for maintaining data accuracy, completeness, consistency, and timeliness across the organization.
• Data Retention and Archiving Policies: These policies govern the retention periods for different types of data and outline the procedures for archiving and disposing of data in accordance with legal and regulatory requirements.
• Data Access and Usage Policies: In 2018, Forrester disclosed that 80% of data breaches are linked to compromised privileged credentials. A data access policy delineates precisely which individuals should possess access to particular assets within your data ecosystem. These policies define who has access to specific data sets, under what circumstances, and for what purposes. They help prevent unauthorized access, misuse, or mishandling of sensitive information. 
• Data Classification and Labeling Policies: To effectively manage and secure data, organizations need to classify and label their data assets based on sensitivity levels, regulatory requirements, and business criticality. These policies provide a framework for consistent data classification and labeling practices.

Data governance policies delineate the framework for overseeing the entire data lifecycle, encompassing aspects like data quality, security, and compliance, thus illustrating the interplay between data governance vs data management.

Real-Life Example

In 2018, a major data breach occurred at Exactis, a Florida-based marketing and data aggregation company, highlighting the critical need for robust data governance policy in USA. The company left a database containing the personal information of nearly 340 million individuals exposed on a publicly accessible server. This massive data trove included sensitive details such as phone numbers, addresses, email addresses, personal interests, and family information, including the number, age, and gender of children.

Fortunately, a security expert discovered the breach and brought it to public attention, preventing further exploitation of the exposed data. This incident underscores the grave consequences of improper data governance and the importance of implementing robust measures to secure personal information.

This example serves as a stark reminder of the significance of data governance for businesses of all sizes and industries. Every organization collects and utilizes data in some capacity, and without proper governance practices, that data is at risk of being misused, lost, or compromised by malicious actors. Moreover, new regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) mandate that companies maintain transparency and accountability in their handling of personal data.

Implementing effective data governance is no longer an option but a necessity for organizations seeking to protect their data assets, maintain customer trust, and avoid legal ramifications or reputational damage. Failure to prioritize data governance practices can lead to severe consequences, whether in the form of cyber threats or regulatory enforcement actions. Proactive measures to ensure data security, privacy, and compliance are crucial for safeguarding an organization’s long-term success and integrity.

           Source: https://llcbuddy.com/data/data-governance-statistics/

Implementing Data Governance Policies

Implementing effective data governance policies requires a comprehensive approach that involves various stakeholders, including data owners, data stewards, and compliance officers.

Here are some key steps in the implementation process within the Governance Risk and Compliance Framework:

• Conduct a Data Inventory and Risk Assessment: Identify and catalog all data assets within the organization, assess their sensitivity and criticality, and evaluate the potential risks associated with non-compliance.
• Establish a Data Governance Committee: Assemble a cross-functional team responsible for developing, implementing, and enforcing data governance policies. This team should include representatives from IT, legal, compliance, and business units.
• Develop and Document Policies: Based on the data inventory and risk assessment, develop clear and comprehensive data governance policies that address relevant regulatory requirements and organizational needs.
• Provide Training and Awareness: Ensure that all employees, contractors, and third-party vendors who handle data are aware of the data governance policies and receive appropriate training on their roles and responsibilities.
• Implement Technical Controls: Leverage data management tools, access controls, encryption, and other technical controls to enforce data governance policies and automate compliance processes where possible.
• Monitor and Audit: Continuously monitor and audit data practices to ensure adherence to the established policies. Regularly review and update policies to align with the evolving regulatory landscape and organizational needs.

Why Choose IntoneSwift?

In an age dominated by data, neglecting the significance of data governance is a perilous oversight. By implementing robust data governance policies and data governance framework, organizations can not only ensure regulatory compliance but also foster a culture of data responsibility, minimize risks, and unlock the full potential of their data assets. Effective data governance is a crucial component of a successful data management strategy and a key enabler for organizations to thrive in the digital age.

Remember, in today’s digital terrain, having data isn’t sufficient; adept management is important. IntoneSwift is one such tool that is perfectly attuned to cater to all your data governance needs. It offers:

• Knowledge graph for all data integrations done
• 600+ Data, and Application and device connectors
• A graphical no-code low-code platform.
• Distributed In-memory operations that give 10X speed in data operations.
• Attribute level lineage capturing at every data integration map
• Data encryption at every stage
• Centralized password and connection management
• Real-time, streaming & batch processing of data
• Supports unlimited heterogeneous data source combinations
• Eye-catching monitoring module that gives real-time updates

Contact us to learn more about how we can help you!