As discussed in my previous post, Data Governance is a mandatory framework to manage and maintain a data-driven organization. Data governance is the beating heart of all your data management processes
Because of the sensitivity of data and the possible misinterpretation, you require consistent and qualitative data that is securely stored and compliant with all laws and regulations, which is why it is essential to set up a Data Governance Framework which is also continuously maintained and updated.
This post continues what we started in the last part, where I discussed two of the five pillars of the Data Governance Framework, Data Quality Management and Data Access Control. I will now guide you through the three remaining pillars of Data Governance, Data Retention and Disposal, Data Security, and Data Compliance. Let’s go!
Data Retention and Disposal
Data retention refers to the period that a company or organization keeps records and data on its customers or clients. Data retention is essential in data governance as it helps organizations comply with legal and regulatory requirements, such as data protection and privacy laws. Data retention policies and procedures allow organizations to determine how long they need to keep certain types of data, such as personal or sensitive information, and how to dispose of it properly.
Data retention is also crucial for managing risk and ensuring that an organization can meet its business and operational needs. For example, suppose an organization needs to retain certain data types for audit or legal purposes. In that case, you will need robust data retention policies and procedures to ensure that the data is protected and accessible when needed. Data governance involves creating and enforcing policies, procedures, and standards that govern data management and usage, and data retention is one of the vital aspects of Data Governance.
Data disposal, also known as data destruction, refers to securely deleting or destroying data that is no longer needed or that you must retain. With data disposal, you aim to ensure that confidential or sensitive information is not exposed or compromised. Doing this prevents unauthorized access, use, or disclosure of the data and complies with legal and regulatory requirements for data protection and privacy. You can accomplish data disposal using different methods, such as physical destruction, overwriting, or degaussing (using a magnetic field to erase data from a storage device).
Data Security
Data security plays a crucial role in your Data Governance Framework. Data security aims to ensure data confidentiality, integrity, and availability and comply with legal and regulatory requirements for data protection and privacy.
Data security in Data Governance involves implementing various technical and organizational measures to protect data. Examples of actions to protect your data:
- Access control. Restricting access to data to authorized individuals or systems by setting up a structure of roles based on the least privilege principle.
- Encryption. With data encryption, you scramble data to be unreadable to unauthorized parties.
- Backup and disaster recovery. With a backup and disaster recovery plan, you set up a goal of creating copies of data and having the plan to restore it in case of an incident. However, a plan is insufficient: it should also be tested regularly by dry-running the backup process.
- Data loss prevention. By implementing a data loss prevention system, you monitor your data usage and identify and block unauthorized data transmissions
- Incident response. By setting up a good plan for responding to and recovering from security breaches, you reduce data loss in case of a breach. Make sure to simulate incident response regularly.
Briefly summarised, data security is essential to your Data Governance framework as it ensures that data is protected and can be trusted. Protecting your data is vital to maintain the organization’s reputation, avoiding legal penalties, and protecting the rights of the data subjects.
Compliance
Compliance plays a critical role in Data Governance. Compliance refers to laws, regulations, standards, and policies governing data collection, storage, use, and disposal. To protect sensitive or confidential data, ensure the privacy of individuals, and avoid legal penalties, compliance is essential for organizations.
Identifying and understanding relevant laws, regulations, standards, and policies that apply to the organization’s data is essential to your compliance strategy in Data Governance. Additionally, you implement policies and procedures to comply with these laws, regulations, standards, and policies.
On top of that, you should regularly assess and monitor compliance with these laws, regulations, standards, and policies. You also should keep records of compliance activities, make them available for audit, and have the plan to address non-compliance and report it.
Examples of laws and regulations that organizations may need to comply with include General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA), and the Sarbanes-Oxley Act (SOX).
Compliance is crucial to data governance as it ensures that you handle data legally and ethically and respect the data subjects’ rights. It also helps the organization avoid penalties and maintain the trust of the stakeholders.
AI and Compliance
Because of the increasing laws and regulations, AI may help your organization with this critical pillar of Data Governance.
AI can automate compliance checks. You can use AI to automate checking data against laws, regulations, standards, and policies, helping your organization quickly to identify and address non-compliance issues.
AI can also help in risk assessment and management. AI can analyze data and identify potential security and privacy risks, allowing your organization to identify potential vulnerabilities and take proactive measures to mitigate them.
You can also use AI for data classification and labeling to automatically classify and label data based on its sensitivity and compliance requirements. Classifying and labeling can help an organization ensure that sensitive data is adequately protected and that you restrict data access to authorized individuals.
AI can also assist in your auditing and reporting process. You can use AI to monitor data usage and generate data access, storage, and disposal reports, helping your organization to demonstrate compliance with laws and regulations and meet audit requirements.
A final application for AI is identifying and preventing data breaches. You can use AI to analyze network traffic, logs, and other data sources to detect suspicious activity, such as data breaches which supports your organization to respond quickly to data breaches and minimize the damage.
AI can help organizations with Data Governance compliance by automating compliance checks, identifying and mitigating risks, classifying and labeling data, auditing, and reporting, and identifying and preventing data breaches. AI can help you to stay compliant with an increasingly complex world of laws and regulations and protect sensitive data from unauthorized access or misuse.
Why all this “Bureaucracy”?
Many people wonder why governance frameworks are necessary. It increases bureaucracy and, because of this, limits the agility of an organization. But don’t underestimate the strengths of bureaucracy. Bureaucracy serves its purpose for a few core reasons.
First, there is efficiency. Bureaucratic processes and procedures provide a structured and organized system for decision-making and the execution of tasks, helping an organization to increase efficiency and productivity. Many say that bureaucracy creates inefficiency but strengthens efficiency when executed properly.
Bureaucracy can also help to ensure that policies and procedures are followed, which can help prevent mistakes and ensure compliance with laws and regulations. Because bureaucracy has a transparent chain of command and accountability, it can help you ensure that your employees complete their tasks and fulfill their responsibilities.
We all strive for fairness and equality, and bureaucracy can help to ensure that decisions are made objectively and fairly by providing clear guidelines and procedures for decision-making. These guidelines and procedures also create transparency: a system for recording and documenting decisions and actions that can help you to ensure transparency and accountability throughout your organization. With this, a stable and predictable system is built based on a clear set of rules and procedures that help to ensure continuity and stability in the face of change.
Finally, with bureaucracy, you can foster specialization of tasks, leading to better expertise and overall efficiency of your organization.
Bureaucracy is not the opposite of agility. When you embrace bureaucracy in an agile organization and utilize the benefits of bureaucracy, it will increase the effectiveness of the agile organization. Ultimately, all people need rules and guidelines to create stability and clarity.
Final Thoughts
Data Governance can help ensure that data is accurate, consistent, and reliable by implementing validation of data, verification of data, and standardization processes. Data Governance can also help to protect sensitive data by implementing security controls, such as access controls, encryption, and monitoring. It can help to improve the efficiency of data-related processes by standardizing data definitions, creating data dictionaries, and implementing data lineage. The Data Governance framework can also help your organization meet regulatory requirements by implementing data retention, archiving, and destruction processes. Data governance creates a culture of data-driven decision-making and improves data sharing and collaboration across an organization while securing transparency and accountability in data management.
Data Governance is a tool of bureaucracy that, as stated before, might have a negative ring for some people but can strengthen your organization if appropriately utilized, helping organizations to make better decisions by providing accurate, reliable, and up-to-date data.
Feel free to contact me if you have questions or in case you have any additional advice/tips about this subject. If you want to keep me in the loop if I upload a new post, make sure to subscribe, so you receive a notification by e-mail.
