Data is a double-edged sword. It’s a valuable business asset, offering crucial insights into market trends, consumer behavior, and operational efficiency. In short, data helps companies make informed decisions, drive innovation, and gain a competitive advantage.

At the same time, data poses considerable risks to organizations. From the looming threat of data breaches and cyberattacks to the intricacies of regulatory compliance, managing data can be challenging. And when mismanaged, data has the potential to harm business reputations, disrupt operations, and lead to severe legal consequences. So, while data holds immense potential, businesses must remain vigilant about risk and navigate the digital landscape cautiously.

In this blog, we’ll consider how organizations can control data risks and improve compliance by adhering to best practices for data management.

What data compliance issues should companies have on their radar?

Data compliance laws are designed to protect individuals’ privacy and ensure the integrity and security of sensitive information. Adhering to these regulations is essential not only for legal reasons but also for maintaining trust with customers and partners. Effective data management practices are pivotal in achieving and sustaining compliance with these complex laws and standards.

For data governance and information management professionals, here’s a summary of three data privacy laws that you should know about.

The Health Insurance Portability and Accountability Act (HIPAA)

HIPAA protects patients’ medical information. This law sets standards for the confidentiality, security, and integrity of protected health information (PHI). It requires organizations to implement three kinds of safeguards to protect data:

• Administrative: Policies, procedures, and measures that manage the selection, development, implementation, and maintenance of security measures to protect PHI
• Physical: Measures that limit access to facilities and devices where PHI is stored
• Technical: Policies and procedures that control technology usage, such as access, audit, and integrity controls

Noncompliance can result in fines from $100 to $50,000 per violation, with a maximum penalty of $1.5 million per year for violations of the same provision.

The European Union’s General Data Protection Regulation (GDPR)

The GDPR safeguards European residents’ personal information, regardless of where it is stored, to protect their privacy. Companies using EU residents’ data must obtain clear consent for data processing and provide transparent information about data usage. They must also give data subjects the right to access, correct, erase, and move their data. Companies must also assess and mitigate risks associated with data processing activities.

Failure to comply with the GDPR can lead to fines as high as €20 million or 4% of the company’s global annual revenue, whichever is higher.

The California Consumer Privacy Act (CCPA)

The CCPA grants California residents rights regarding their personal information held by businesses, including the right to know, delete, and opt out of the sale of their personal information. Organizations must understand what personal information they collect, process, and share, and implement reasonable security practices to protect consumer data.

Businesses that fail to comply with the CCPA can be fined up to $7,500 for intentional violations. Consumers also have the right to sue for data breaches if the business fails to implement reasonable security practices.

But data management doesn’t just help companies maintain a minimal degree of compliance; it can also create strategic advantages.

What are the benefits of strong data management practices?

Robust data management practices meet regulatory requirements — and they also have a series of other benefits for organizations, creating a foundation for sustainable growth.

One immediate, tangible benefit of better data management is avoiding hefty penalties and fines for noncompliance. For example, regulatory bodies, such as the U.S. Department of Health and Human Services, can levy staggering fines for HIPAA breaches that hurt a company’s financial stability.

Data privacy laws like the GDPR and CCPA often grant individuals the right to access their personal data. Robust data management means organizations can quickly respond to these requests. A well-organized data repository ensures that the right data can be identified and collected promptly.

Efficient data management processes also streamline operations. Automated compliance checks and reporting mechanisms save time and effort, allowing employees to focus on strategic tasks that contribute to an organization’s growth.

Further, proper data management helps organizations mine information for valuable insights. Informed decision-making, based on accurate data, can guide business strategies, product development, and customer engagement, enhancing overall business performance.

Finally, in a time where data breaches and privacy concerns are regular headlines, organizations that demonstrate a commitment to data security and compliance gain a competitive edge. Clients, business partners, and other stakeholders are more inclined to collaborate with companies that prioritize data protection. Compliance certifications and transparent data management practices can be powerful marketing tools, setting businesses apart in a crowded marketplace.

What else can businesses do to ensure data compliance? Let’s look at a few best practices.

What data management best practices can improve data compliance?

Implementing effective data management practices is essential for achieving and maintaining data compliance. Here are some key steps to follow.

1. Establish a data governance framework

A data governance framework defines the policies, procedures, roles, responsibilities, and processes for managing and protecting the quality and availability of an organization’s data. This framework should establish guidelines and best practices for managing data assets, align data-related activities with business objectives, and ensure compliance with regulations and industry standards.

A comprehensive data governance framework typically includes the following components:

• Data ownership: Clearly defined roles and responsibilities for data owners who are accountable for specific data assets
• Data quality standards: Standards and metrics to measure and maintain data accuracy, completeness, consistency, and reliability
• Data security policies: Guidelines for data encryption, access controls, data masking, and other security measures to protect sensitive data

Organizations should document and update their data management policies and procedures to reflect changes in regulations and technologies.

2. Understand your data with a data inventory and data map

To effectively manage your data, you must know what data you have and where that data is stored.

First, inventory your organizational data. What data are you routinely generating? Consider not only employee-created data but also automatically generated data from sources like video cameras or smart sensors.

Next, create a data map to track where each type of data is stored and how it is used. Data mapping is the process of identifying and documenting how data moves within an organization. This will help you understand where data is stored, processed, and transmitted.

Once you’ve prepared a data map, classify your data based on its sensitivity. Potential categories include personal data, financial records, and protected health information. Machine learning algorithms can expedite this process by automatically classifying and tagging sensitive data for special handling. With this information in hand, you can apply appropriate security measures.

Understanding how and where data flows will help you minimize the collection and retention of unnecessary personal data. The GDPR emphasizes data minimization, and data mapping identifies extraneous data collection points. Data mapping will help you pinpoint personal data quickly when data subjects exercise their rights under the GDPR and CCPA.

3. Streamline data storage with a centralized data repository

Integrating data from various sources in one place offers a single point of access for all authorized users. This simplifies data retrieval, reducing the time and effort needed to locate specific information. Advanced solutions synchronize data continuously and offer real-time data access, reducing the risk of outdated or conflicting information.

Centralized repositories offer a comprehensive view of all data assets. This visibility is crucial for effective data management, giving organizations an understanding of their data landscape from which they can make informed decisions. Centralized storage also facilitates end-to-end data lifecycle management, including data creation, retention, usage, archival, and disposal. This ensures a systematic approach to managing data throughout its lifecycle.

4. Follow a strict information governance policy that defines data retention periods

When adhered to, strong information governance policies and processes can reduce the amount of data in an organization, which limits the amount of data that may create risk or require disclosure in audits, investigations, and litigation.

Information governance ensures that organizations create and enforce data retention schedules so they retain data only as long as required, preventing both noncompliance due to early deletion and the risks of over-retention.

Information governance policies also guide the secure deletion or anonymization of data when it’s no longer needed, reducing the risk of data breaches.

5. Implement data security measures

You should also conduct security audits and vulnerability assessments to identify and address potential weaknesses. Multiple layers of data security are necessary to protect data from physical and network intrusions. Encrypt data at rest and in transit to protect it from unauthorized access. Role-based access controls can limit access to sensitive data to authorized users.

A well-defined incident response plan can help quickly mitigate data breaches or security incidents. Once your plan is in place, run drills to ensure that employees are prepared to respond effectively in the event of a data breach.

6. Train employees on data management protocols

Provide comprehensive training to employees about data compliance regulations, data security best practices, and their roles and responsibilities. The stronger the culture you build around data management and data security, the more vigilant employees will be about practicing good data hygiene.

7. Conduct regular audits

Effective data management is a complex and continuously evolving topic, driven by changes in both data technology and applicable laws and regulations. So, set a cadence for audits to review your data management practices, and monitor for any new laws or regulations that may require an update. Third-party auditors or consultants can assess your organization’s compliance status and make recommendations for improvement.

Learn more about how to effectively manage your data

Strong data management is the cornerstone of achieving and maintaining compliance with data privacy laws and regulations. By investing in well-designed data management practices, you can safeguard sensitive information, avoid legal pitfalls, and maximize the value of your data assets while minimizing data risks.

Get expert insights for adopting a cross-functional approach to data management in our webinar, “Declutter your data: Strategies for efficient data retention & risk reduction.” Watch now on-demand.