Webinar: Designing Storage Architectures for Data Privacy, Compliance and Governance
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The document discusses the challenges and strategies for designing storage architectures that ensure data privacy, compliance, and governance, particularly in relation to GDPR and similar regulations. It addresses issues like data quality, consent management, and the need for data centers to evolve towards intelligent data governance. Key focus areas include the right to rectification, data portability, and the role of archives in regulatory compliance.
Webinar: Designing Storage Architectures for Data Privacy, Compliance and Governance
- 1. Designing Storage Architectures for Data Privacy, Compliance and Governance For audio playback and Q&A go to: bit.ly/StorageArchPrivacy
- 2. OurSpeakers Scott Baker Sr. Director, Content and Data Intelligence George Crump, Founder and Lead Analyst
- 3. In Regulations We Trust
- 4. The Big and Personal Data of the Digital Citizen ● The Impact of GDPR and Data Privacy ○ More than a European Problem ■ Many countries and US States are considering or have adopted similar regulations
- 5. The Most Common Challenges Business Face Requirement Challenges Transparency Guarantees harder with heterogeneous and silo’ed technology Data Quality Tracking data across workloads and geographies with instant ability to erase data if consent is withdrawn Enforcement of Privacy Proving one, or more, data protection action(s) required if asked Data Breach Preparedness Data silos cause challenges with collecting incident details and taking action Rights of the Digital Citizen Consent, purpose, intent, protection, and secure destruction of all personal data retroactively
- 6. The Data Governance Gap - Real World Impact TIME EXPECTED >37%: MOBILE 75%: UNUSED <15%: CLASSIFIED <10% HAVE CDO Data Governance GAP REALITY REFERENTIALVALUEOFDATA (+) (-) WHAT? WHERE? WHAT TO DO WITH IT? WHO’S RESPONSIBLE?
- 7. Data Centers Must Evolve from Data Protection to Data Management
- 8. Backups - Move to a Secondary Role ● Short retention (weeks, even days) ● Primary purpose is to recover the most recent copy of data ● Critical apps protected by replications, snapshots and copy data management products
- 9. Archives - Taking a Leading Role ● Long term retention ○ Primary purpose is to meet regulations and compliance ○ Requires a shift from disk backup or Big NAS ○ Must be searchable and granular
- 10. Moving From Data Governance to Intelligent and Value-Based Governance
- 11. What is Driving the Urgency for Data Governance DATA VOLUME REACTIVE APPROACHES LACK OF PROCESSES FRAGMENTED OWNERSHIP LACK OF SKILLS TECHNOLOGY SILOS
- 12. Closing the Data Governance GapREFERENTIALVALUEOFDATA (+) (-) GAIN VISIBILITY UNDERSTAND TAKE CONTROL TIME
- 13. Data Services to Enable Intelligent Data Governance Available Insightful Actionable
- 14. © Hitachi Vantara Corporation 2018. All Rights Reserved Modeling for Value-Based Governance
- 15. Data Governance: Data Ingest & Aggregate Start Determine Type Collect Contents Contains PII Yes Categorize PII Mark Sensitive Migrate to HCP No Preserve Yes Smooth, Augment Normalize No Leave In Place Destroy No Yes Apply Custom Retention Policy Central Index Hitachi Content Search Mobilize / Make Portable
- 16. Data Governance: Right to Rectification Index 1 Hitachi Content Search Index 2 Index N Start Result Set User Interface Rectify On HCP? Yes Can Modify Yes No Audit Request No Issue Ticket (ServiceNOW) No Audit Request & Inform Subject Yes Modify Update Indexes with Modified Data
- 17. Content Intelligence: Right to be Forgotten Start Data Erasure Requested On HCP Legally Retained Yes Rules Override No No Issue Ticket (ServiceNOW) Yes Deny & Log Details Yes Deny & Log Details No Collect All Data Via Criteria – For Each Document Is it Mobile Yes Remove from HCP Anywhere No Destroy Notify SubjectUpon Completion (destroyed or not)
- 18. Data Governance: Right to Data Portability Start Data Portability Requested Read File No Send to Content Intelligence Yes Extract All Relevant Data Write Data to New File in XML Collect All Data Via Criteria – For Each Document Create Dynamic HCP/AW Space Notify Subject Legal Retained Log Details Yes Store Transformed Data (as XML file) In HCP/AW Space Include Report of Data that could not be included for legal hold reasons.
- 19. © Hitachi Vantara Corporation 2018. All Rights Reserved Intelligent Data Governance in Action
- 24. © Hitachi Vantara Corporation 2018. All Rights Reserved Behind the Scene: Realtime Data Profiling
- 27. © Hitachi Vantara Corporation 2018. All Rights Reserved Behind the Scene: Data Enrichment and Data Redaction
- 32. Data Services to Enable Intelligent Data Governance Available Insightful Actionable
- 33. Thank you! Storage Switzerland http://www.storageswiss.com [email protected] StorageSwiss on Twitter: http://twitter.com/storageswiss StorageSwiss on YouTube: http://www.youtube.com/user/storageswiss Hitachi https://www.hitachivantara.com Hitachi on Twitter: https://twitter.com/HitachiVantara Hitachi on Facebook: https://www.facebook.com/HitachiVantara/
- 34. Designing Storage Architectures for Data Privacy, Compliance and Governance For complete audio and Q&A please register for the On Demand Version: bit.ly/StorageArchPrivacy
Editor's Notes
- #6: SPEAKER SCRIPT GDPR
- #12: SPEAKER SCRIPT The drivers behind the need for a more intelligent approach to data governance should be obvious. You hear them mentioned all the time – growth, speed, variety, and veracity of data. But there is so much more that is creating a sense of urgency for better data management and governance. To highlight a few that are affecting the way our customers are do business today, consider the following: The growth of data is constant – leaving organization’s continually facing the challenges of aggregating, managing, governing, and creating new value from their data Organizations don’t often realize there is a problem with their data in advance of a situation. Reacting creates in-the-moment data management solutions that fail to scale as the business grows, applications change, and new data formats are adopted A lack of processes, data management systems, and inadequate data strategies contribute toward data quality issues and untrustworthy data sets. Lack of data ownership is a key shortfall for most organizations. This fragmentation is often across different departments and stakeholders, versus the business as a whole. Many organizations are unable to invoke enough support to improve their data culture. This is often driven by a lack of knowledge or skillset on the proper techniques to manage data effectively. Lastly, reactive approaches, incomplete processes, fragmented data ownership, and insufficient skills are catalysts that foster single-purpose solution adoption that ultimately traps data in technology silos that ultimately increase compliance and productivity risks for the business