Domain Management Best Practices for Data Privacy

Even without a state privacy law - New York is coming after your website tracking (and so can other states). Key points from a new advisory by the Office of the New York State Attorney General based on an investigation of websites: As we've been telling clients - Even without a state privacy laws, businesses’ privacy-related practices and statements are subject to a state's consumer protection laws that prohibit businesses from engaging in deceptive acts and practices. Mistakes to avoid: 🔹 Make sure that your cookie management tool does not leave uncategorized or miscategorized tags/cookies. 🔹 Make sure your cookie management tool works well with your tag management tool. (disabling tracking in one disables the other too). 🔹 Make sure your marketing or advertising tags work as described and DO NOT remain active even after visitors try to disable them using the sites’ privacy controls. 🔹 Ensure even tags that are hardcoded to the website get deactivated by the cookie management tool. 🔹 Do not rely on contract based restrictions like limited data use (LDU - Meta) or Restricted data processing (RDP - Google) in states where they don't actually work. 🔹 Before deploying a new tag, understand what data the tag collects and how the data may be used or shared. 🔹 Address NON cookie based sharing Things to do: Configuration of trackers: 🔹 Designate a qualified individual (or individuals) with appropriate training to be responsible for implementing and managing website-tracking technologies. 🔹 Before deploying a new tag or tool, or changing how an existing tag or tool is used, take appropriate steps (including active due diligence) to identify the types of data collected and how the data will be used and shared. 🔹 When deploying a new tag or tool, or changing use, ensure that it is appropriately categorized and configured. 🔹 Conduct appropriate testing (regularly and following a change) to ensure that tags and tools are operating as intended. 🔹 Conduct reviews on a regular basis to ensure tags and tools are properly configured Disclosure and interface: 🔹 Make sure that your representations on the website about privacy controls (whether express or implied through privacy controls configuration) are accurate 🔹 Avoid language that creates a misleading impression of how your website handles tracking and choice [Don't say "by clicking accept cookies" you accept - if the cookies deploy by default] 🔹 Ensure the user interface is not misleading - beware of dark patterns (e.g a faded gray color, and without any visual indication that the words could be clicked); ambiguous buttons. 🔹 If you can agree with a single click you should be able to opt out with single click. 🔹 Make the interface accessible (e.g. allow navigation of privacy controls with a keyboard to tab) 🔹 Don't use large blocks of text or complicated language #dataprivacy #dataprotection #privacyFOMO https://rb.gy/bei7cu

On a near weekly basis, I read about breaches where much of the exfiltrated data was old data that the organization had no real reason to retain. See, e.g., https://lnkd.in/eaX53AWQ and https://lnkd.in/e4pVA6bT. According to IBM's 2023 Cost of a Data Breach Report, breaches cost organizations an average of $165 per record breached. Report at 2. That means that purging 100,000 records of unnecessary data could save you $16.5M in the event of a breach. Here are five tips: 1. PRACTICE DATA MINIMIZATION: Organizations should practice "data minimization." This means only collecting data that you have a good business reason for collecting and purging unneeded data when it is no longer needed. 2. ARCHIEVE DATA OFFLINE: In one recent example, the breached company apparently "ceased operations in December 2022 but, to comply with legal obligations, . . . maintained an archived copy of data previously stored on its computer systems." See https://lnkd.in/e4pVA6bT. To the extent you are only retaining old data is to satisfy regulatory requirements or just "in an abundance of caution," consider storing the data completely offline, so it is less likely to be breached. 3. CONDUCT A DATA MAPPING: These days it is common for data records to be duplicated in many places across an organization. Thus, consider conducting a regular "data mapping" to ensure that you know where all of your sensitive data is located, that you are adequately protecting it, and that you are purging it when appropriate. 4. IMPLEMENT A WRITTEN POLICY: Be sure to document your data retention and destruction policy in a written policy, and train your employees on the policy regularly. Remember to update the policy to reflect the changing realities in your organization. 5. OVERSEE THE DESTRUCTION OF DATA: Finally, when you destroy data, take reasonable steps to ensure that the data is actually being destroyed. One bank was recently fined $60M for failing to properly oversee a vendor responsible for purging personal data from digital devices. See https://lnkd.in/eutKzpU7.

𝗚𝗥𝗖 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗚𝗥𝗖 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀: 𝟭. 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲:   - Data ownership and stewardship   - Data classification and categorization   - Data policies and procedures   - Data quality and integrity 𝟮. 𝗥𝗶𝘀𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁:   - Data security and privacy risks   - Data breaches and loss   - Data compliance and regulatory risks   - Data quality and integrity risks 𝟯. 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲:   - Regulatory compliance (e.g., GDPR, CCPA, HIPAA)   - Industry standards compliance (e.g., ISO 27001, NIST CSF)   - Data protection and privacy laws 𝗢𝗯𝗷𝗲𝗰𝘁𝗶𝘃𝗲𝘀: 1. Ensure data accuracy, completeness, and consistency 2. Protect sensitive data and maintain confidentiality 3. Comply with regulatory requirements and industry standards 4. Mitigate data-related risks and threats 5. Improve data quality and integrity 6. Enable data-driven decision-making 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀: 1. ISO 27001 (Information Security Management System) 2. NIST Cybersecurity Framework 3. #COBIT (Control Objectives for Information and Related Technology) 4. GDPR (General Data Protection Regulation) 5. CCPA (California Consumer Privacy Act) 6. HIPAA (Health Insurance Portability and Accountability Act) 𝗧𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: 1. Data Governance platforms (e.g., Collibra, Informatica) 2. Data Quality and Integrity tools (e.g., Trillium, Talend) 3. Data Security and Encryption solutions (e.g., Symantec, McAfee) 4. Data Loss Prevention (#DLP) systems 5. Data Analytics and Visualization tools (e.g., Tableau, Power BI) 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: 1. Establish clear data ownership and stewardship 2. Develop data policies and procedures 3. Implement data classification and categorization 4. Conduct regular data risk assessments 5. Monitor data quality and integrity 6. Provide ongoing data governance training 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀: 1. Data complexity and volume 2. Regulatory complexity and compliance 3. Limited resources and budget 4. Insufficient data governance framework 5. Data quality and integrity issues 𝗚𝗥𝗖 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀: 1. Improved data quality and integrity 2. Enhanced regulatory compliance 3. Reduced data-related risks 4. Increased data-driven decision-making 5. Better data security and privacy 6. Improved business outcomes 𝗥𝗼𝗹𝗲𝘀 𝗮𝗻𝗱 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: 1. Chief Data Officer (#CDO) 2. Data Governance Manager 3. Data Steward 4. Data Quality Analyst 5. Compliance Officer 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: 1. Certified Data Governance Specialist (#CDGS) 2. Certified Information Systems Security Professional (#CISSP) 3. Certified Data Quality Analyst (#CDQA) 4. Certified Risk and Information Systems Control (#CRISC) 5. ISO 27001 Lead Auditor 𝗪𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗹𝗶𝗸𝗲 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗼𝗻 𝗚𝗥𝗖 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗼𝗿 𝗿𝗲𝗹𝗮𝘁𝗲𝗱 𝘁𝗼𝗽𝗶𝗰𝘀? #GDPR #CCPA #GRC

Strengthening Data Protection in your organization 🔒🛡️🔑🚨 Below list provides a robust data protection measures is paramount in safeguarding organizational assets and maintaining trust with stakeholders. 1. Understanding Data Protection Fundamentals: Define the importance of data protection and its significance in preserving confidentiality, integrity, and availability of sensitive information. Explain regulatory compliance requirements, such as GDPR, CCPA, HIPAA, and others, and their implications for data protection strategies. 2. Data Classification and Risk Assessment: Discuss the importance of data classification to prioritize protection efforts based on data sensitivity and risk levels. Highlight the role of risk assessments in identifying vulnerabilities, threats, and potential impact on data assets. 3. Implementing Robust Security Controls: Explore the implementation of encryption, access controls, authentication mechanisms, and audit trails to protect data from unauthorized access and breaches. Discuss the benefits of endpoint security solutions, network segmentation, and secure configuration management in enhancing data protection measures. 4. Data Loss Prevention (DLP) and Incident Response: Explain the role of DLP solutions in preventing data leaks, monitoring data usage, and enforcing security policies. Outline incident response procedures, including detection, containment, investigation, and recovery, to mitigate the impact of data breaches. 5. Employee Training and Awareness: Emphasize the importance of cybersecurity awareness training for employees to recognize phishing attacks, social engineering tactics, and data protection best practices. Encourage a culture of security awareness and accountability across the organization. 6. Continuous Monitoring and Auditing: Stress the significance of continuous monitoring, threat intelligence, and security audits to detect anomalies, suspicious activities, and potential security incidents. Discuss the role of security metrics, reporting, and compliance audits in evaluating the effectiveness of data protection measures. 7. Collaboration and Information Sharing: Advocate for collaboration with IT teams, stakeholders, industry peers, and cybersecurity communities to share insights, best practices, and threat intelligence. Promote participation in cybersecurity forums, conferences, and knowledge-sharing platforms to stay updated on emerging threats and trends. 8. Future Trends and Emerging Technologies: Discuss the impact of emerging technologies such as artificial intelligence (AI), machine learning (ML), blockchain, and secure cloud solutions on data protection strategies. #DataProtection #CybersecurityAdvocacy #InfoSec #DataSecurity #SecureYourData #CyberAware #SecurityFirst #DataPrivacy #ProtectYourAssets

Data is every organization’s most valuable asset, but it is also the most targeted. Whether you are managing pipelines, warehouses, or APIs, data security is not optional, it is a necessity. Here are 15 best practices every data engineer must follow to keep systems safe and compliant 👇 1. Encrypt Data at Rest and In Transit Use strong encryption algorithms to secure data during storage and transmission, preventing unauthorized access. 2. Implement Role-Based Access Control (RBAC) Grant permissions based on roles to ensure that only authorized users can access specific datasets. 3. Use Strong Authentication Mechanisms Enable multi-factor authentication (MFA) or OAuth for enhanced user and system security. 4. Mask Sensitive Data in Non-Production Environments Hide confidential information during testing and staging to stay compliant with data privacy standards. 5. Regularly Rotate Access Keys and Credentials Update passwords, tokens, and API keys periodically to minimize unauthorized access risks. 6. Audit and Monitor Data Access Logs Continuously track who accesses what data to detect unusual or suspicious activity early. 7. Apply the Principle of Least Privilege Grant users only the permissions required for their tasks — nothing more, nothing less. 8. Secure Data Pipelines and APIs Protect data transfers using HTTPS, tokens, and strong authentication protocols. 9. Regularly Patch and Update Systems Keep servers, databases, and tools up to date to close potential security vulnerabilities. 10. Implement Network Segmentation Isolate sensitive databases within secure network zones to reduce exposure in case of breaches. 11. Use Data Loss Prevention (DLP) Tools Monitor and control data transfers to prevent leaks, misuse, or policy violations. 12. Backup Data Securely and Frequently Maintain encrypted backups and test recovery plans regularly to ensure business continuity. 13. Follow Compliance Frameworks (GDPR, HIPAA, etc.) Stay aligned with legal and industry standards for data collection, processing, and sharing. 14. Conduct Periodic Security Audits and Penetration Tests Identify vulnerabilities proactively through regular testing and security reviews. 15. Educate Teams on Data Security Practices Train employees to recognize threats, use data responsibly, and adhere to secure handling policies. Data breaches do not happen overnight, they result from overlooked basics. Start embedding these 15 practices today to protect your systems, ensure compliance, and build lasting trust in your data infrastructure.