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Designing Storage Architectures for Data
Privacy, Compliance and Governance
For audio playback and Q&A go to:
bit.ly/StorageArchPrivacy
OurSpeakers
Scott Baker
Sr. Director, Content
and Data Intelligence
George Crump,
Founder and
Lead Analyst
In Regulations We Trust
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
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ability to erase data if consent is withdrawn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
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?
Data Centers Must Evolve from
Data Protection to Data Management
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
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
Moving From Data
Governance to Intelligent
and Value-Based
Governance
What is Driving the Urgency for Data Governance
DATA
VOLUME
REACTIVE
APPROACHES
LACK OF
PROCESSES
FRAGMENTED
OWNERSHIP
LACK OF
SKILLS
TECHNOLOGY
SILOS
Closing the Data Governance GapREFERENTIALVALUEOFDATA
(+)
(-)
GAIN VISIBILITY
UNDERSTAND
TAKE
CONTROL
TIME
Data Services to Enable Intelligent Data Governance
Available Insightful Actionable
© Hitachi Vantara Corporation 2018. All Rights Reserved
Modeling for Value-Based Governance
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
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
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)
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.
© Hitachi Vantara Corporation 2018. All Rights Reserved
Intelligent Data Governance in Action
© Hitachi Vantara Corporation 2018. All Rights Reserved
Behind the Scene:
Realtime Data Profiling
© Hitachi Vantara Corporation 2018. All Rights Reserved
Behind the Scene:
Data Enrichment and Data Redaction
Data Services to Enable Intelligent Data Governance
Available Insightful Actionable
Thank you!
Storage Switzerland
http://www.storageswiss.com
georgeacrump@storageswiss.com
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/
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

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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
  • 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
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  • 24. © Hitachi Vantara Corporation 2018. All Rights Reserved Behind the Scene: Realtime Data Profiling
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  • 27. © Hitachi Vantara Corporation 2018. All Rights Reserved Behind the Scene: Data Enrichment and Data Redaction
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  • 32. Data Services to Enable Intelligent Data Governance Available Insightful Actionable
  • 33. Thank you! Storage Switzerland http://www.storageswiss.com georgeacrump@storageswiss.com 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

Notas del editor

  1. SPEAKER SCRIPT GDPR
  2. 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