Cloud Data Governance 101

If you’re like most organizations, your data is scattered across the vast expanse of the cloud, accessible from anywhere at any time. Theoretically, this is ideal – having data at your fingertips allows you to work collaboratively, remotely, and efficiently. But along with that freedom comes a slew of risks and challenges that threaten the privacy, security, and integrity of your data.

This is where cloud data governance comes in. In this blog, we’ll give you a primer on cloud data governance so you can implement an effective governance framework that balances data security with accessibility.

What is Cloud Data Governance?

Cloud data governance refers to the frameworks, processes, and policies put in place to ensure cloud data is managed securely and effectively. It establishes guidelines for how data is collected, stored, accessed, and utilized.

The 6 Principles of Cloud Data Governance

Cloud data governance is built upon six key principles, each of which helps maintain order and integrity within data ecosystems:

  1. Data Ownership: Designating clear ownership of data assets and holding individuals and/or departments accountable for their usage.
  2. Data Quality: Ensuring that data is accurate, consistent, and reliable throughout its lifecycle, so it can deliver accurate insights.
  3. Compliance and Regulatory Requirements: Adhering to legislation, industry and/or organizational standards, and contractual obligations to maintain compliance and avoid penalization.
  4. Data Lifecycle Management: Implementing strategies for managing data throughout its lifecycle, including creation, storage, usage, and deletion.
  5. Data Access Control: Restricting access to data based on user, object, environment, and purpose-based attributes to prevent unauthorized access or misuse.
  6. Risk Management and Mitigation: Identifying potential risks and vulnerabilities within the data ecosystem and implementing measures to mitigate them, such as dynamic data masking, data monitoring, or disaster recovery plans.

These principles are the basis for a cloud data governance model that ensures security, compliance, and efficiency in a rapidly evolving digital landscape.

How Cloud Data Governance Is Used In Practice

Now that we have a grasp of what cloud data governance entails, let’s dive into how it plays out in real-world scenarios where data security isn’t just a buzzword, but a critical business concern.

Managing Data Across Regions & Platforms

Imagine a multinational media company operating across geographic regions, each with its own compliance laws and regulations. Typically, juggling data localization laws and policy enforcement across data platforms is both complex and time consuming.

In this scenario, governance frameworks serve as a guiding force, seamlessly balancing cross-platform cloud data management with data security and compliance. By centralizing policies and access controls, you’re able to maintain consistency and compliance across disparate cloud platforms, mitigating the risk of data breaches or regulatory penalties.

Facilitating Collaboration and Data Sharing

For a pharmaceutical company developing new lifesaving drugs, collaborating with hospitals on clinical trials requires equal and authorized data access. However, uneven access controls and concerns about inadvertent data exposure often limit or derail effective data sharing.

With cloud data governance, doctors and researchers securely share and collaborate on sensitive data sets, even those containing personally identifiable information (PII) and protected health information (PHI). Governance frameworks account for data quality, security, and risk management, which gives pharma companies, hospitals, and trial participants alike confidence that data will be used legally, ethically, and efficiently. Cloud data governance fosters a culture of collaboration while safeguarding the confidentiality and security of shared data assets.

Ensuring Data Privacy and Confidentiality

Let’s zoom in on a healthcare organization leveraging cloud technology to streamline patient care and improve outcomes. As with the previous example, handling sensitive health information is fraught with complexity and hesitation. And with good reason – the healthcare and life sciences industry has experienced more frequent and costly data breaches over the past decade-plus than any other field.

With strict standards like HIPAA security compliance governing how PHI is handled, cloud data governance is indispensable. By implementing robust access controls, data obfuscation techniques, and data audit trails, you’ll ensure that sensitive data remains private and confidential, safeguarding both patient trust and regulatory compliance.

Enforcing Regulatory Compliance

We’ve all seen the headlines – following a data breach, organizations face intense scrutiny from both customers and from regulatory authorities. For financial institutions like Swedbank, maintaining compliance with regulations like GDPR or PCI DSS isn’t just something to strive for – it’s an absolute necessity.

Cloud data governance frameworks allow highly regulated organizations to demonstrate a proactive approach to compliance, providing evidence of data access controls, audit trails, and risk mitigation strategies. By aligning with pertinent regulations, you not only avoid hefty fines, but also enhance your reputation as a trusted custodian of sensitive data.

In each of these scenarios, cloud data governance is more than just a theoretical concept — it’s the backbone of secure and compliant data management practices. Putting governance strategies into practice allows you to de-risk data use, so you’re able to navigate the complexities of the digital landscape with confidence and agility.

How to Implement Data Governance and Security

Data security and governance are two sides of the same coin in the realm of data management. Each plays a crucial role in safeguarding valuable data and ensuring compliance with regulatory standards.
The following capabilities are key for implementing cloud data governance and security measures.

1. Data Discovery and Classification

Data discovery plays a pivotal role in cloud data governance and security by providing insights into the data landscape – what data lives where, who owns it, and how sensitive it is.

In the data discovery process, your system will identify and catalog data from across your tech stack, including databases, file shares, and cloud repositories. Having a comprehensive understanding of your data allows you to accurately inventory, assess data quality and integrity, and determine ownership and usage patterns. By leveraging data discovery tools, you’ll lay the foundation for an effective data governance strategy, ensuring that data is managed, protected, and utilized in accordance with regulatory requirements and business objectives.

2. Dynamic Data Access Control and Data Masking

In today’s interconnected world, petabytes of data flow across cloud platforms and organizational boundaries every minute. The human mind is simply incapable of tracking all this movement on its own. Scalable and flexible access controls and masking capabilities are the most reliable ways to stay on top of how that data is being transmitted, accessed, and used.

By enforcing data access controls at the data layer, permissions are granted or restricted in real-time based on contextual factors such as user, environment, and object attributes. Similarly, dynamic data masking obfuscates sensitive information at query time, ensuring that only authorized individuals view and access the necessary data. These controls align to governance frameworks and requisite compliance standards.

3. Continuous Monitoring and Auditing

Data security is an ongoing process that requires continuous monitoring and auditing to detect vulnerabilities and anomalies, as well as ensure compliance.

Governance mechanisms facilitate regular audits, compliance assessments, and risk evaluations to identify gaps in security controls and proactively address them. Coupled with real-time user behavior analytics and sensitive data indicators, you’ll keep a finger on the pulse of data activity. Automated monitoring tools and audit reports help maintain visibility into data access patterns, track changes to sensitive data, and demonstrate compliance with regulatory requirements.

In essence, data security and governance are symbiotic, working hand-in-hand to protect data assets, mitigate risks, and uphold stakeholder trust. By aligning security practices with governance principles, you’ll establish a holistic approach to data protection, laying the foundation for a secure and compliant data environment.

Cloud Data Governance In Action

Cloud data governance is a cornerstone of modern data stacks, providing the framework and tools necessary to navigate the complexities of data management in the cloud era.

From ensuring data security and compliance to facilitating collaboration and informed decision-making, cloud data governance plays a multifaceted role in de-risking data and delivering new value. By embracing best practices in data governance, you’ll mitigate risks, improve data integrity, and build trust with stakeholders, laying the groundwork for sustainable growth and innovation in an increasingly data-driven world.

To take the first steps to establish a cloud data governance framework, download the playbook How to Build a Governance, Risk, and Compliance Framework for Enterprise Data Analytics.