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Simplifying the data privacy governance quagmire building automated privacy programs that actually work!
The document discusses the essential elements of data security and privacy, emphasizing the need for automated privacy programs that effectively address modern challenges. It outlines the distinctions between data security, data privacy, and data protection, while identifying obstacles to building effective privacy programs. Key steps for establishing such programs include understanding regulatory obligations, identifying data assets, and gaining executive support.
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Simplifying the data privacy governance quagmire building automated privacy programs that actually work!
- 1. Title Text Body LevelOne • Body Level Two • Body Level Three • Body Level Four • Body Level Five powered by Simplifying the data privacy governance quagmire: Building automated privacy programs that actually work! Avinash Ramineni Lenin Aboagye
- 2. The Why 01 The What 02 TheHow 03 AGENDA 02
- 3. What is DataSecurity ? 02 ● Data security is focused on protecting personal data from any unauthorized third-party access or malicious attacks and exploitation of data. ● Data security is policies, methods, and means to secure personal data. ● Data / Information security is a prerequisite to data privacy.
- 4. What is DataPrivacy ? 02 ● Privacy is an individual’s right to freedom from intrusion and prying eyes or the right of the person to be left alone. ● Data privacy is about proper ○ Usage ○ Collection, ○ Retention ○ Deletion ○ Storage of data. ● About the rights of individuals with respect to their personal information.
- 5. Data Protection 02 Data protectionis amalgamated data security and data privacy.
- 6. Knowledge of sensitivedata storage is tribal - not institutional. DATA GOVERNANCE 02
- 7. Challenges in buildinga Privacy Program 02 1. Inventory of data assets across all the enterprise 2. Every increasing scale of data 3. Ever changing data landscape 4. Data Hoarding for Big Data/ AI / ML initiatives 5. Balancing monetizing data with managing risk 6. Too many data privacy regulations.
- 8. 01 Data Hoardingfor Big Data/ AI / ML initiatives
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- 10. 01 PRIVACY Regulationsin Works https://iapp.org/media/pdf/resource_center/State_Comp_Privacy_Law.pdf
- 11. ● Current toolsare still focused on solving legacy data security problems ● Fewer security / privacy people have the experience to secure the current unstructured data landscape ● Most security people are not involved in their organization’s big data security initiatives ● Industry lagging behind controls for modern security/privacy landscape Legacy tools not built to address modern data challenges 03 DATA CENTRIC SECURITY GAPS 02
- 12. Discover. Secure. Monitor Buildinga Privacy Program 02
- 13. Steps in buildinga Privacy Program 02 1. Understand Regulatory / Compliance Obligations. 2. Identify the Organization’s Information and Where It’s Located. 3. Gain Executive Support 4. Establish Accountability for the Program. 5. Develop Policy and Training. 6. Ensure Third-Party Compliance. 7. Integrate the Program into Governance. 8. Implement Privacy Impact Assessments and Mitigation Plans.
- 14. 4 Pillars ofData Privacy DATA LANDSCAPE 01
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- 16. CCPA | GDPRCompliance 03 02
- 17. Data Subject Catalog| CCPA & GDPR 03 02
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