The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Resilience

Data without the drama™
Capital One
The Data Trifecta
WEBINAR
Privacy, Security & Governance Race
from Reactivity to Resilience
Awah Teh
Vice President of
Data Governance &
Privacy Engineering
Joseph Sommer
Data & Analytics,
Managing Partner
Steve Prestidge
Chief Commercial &
Innovation Officer
EY Anonos

© Anonos 2023 |
OIL
Single-Use Asset
Increase Innovation & Profits by Several Magnitudes
2

© Anonos 2023 |
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ulti-Use
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Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
WATER
Generative,
Multi-Use Asset
OIL
Single-Use Asset
VS.
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© Anonos 2023 |
Misconception
4
Reactive versus proactive
enterprise functions
Historically, organizations have viewed
“reactive” functions like privacy, security,
and governance as being antithetical to
“proactive” functions such as analytics
and data innovation.

© Anonos 2023 |
Reality
5
Reactive and proactive
functions share dependencies
Privacy, security, and governance are needed
to achieve both reactive and proactive
functions: the underpinning mechanisms are
the same.

© Anonos 2023 |
Enterprise data governance efforts have both proactive and reactive benefits
Top reported benefits of data governance initiatives highlight maximizing the business utility of data
38%
37%
30%
26%
26%
25%
24%
23%
23%
17%
13%
1%
2%
8%
Faster access to relevant data
Higher quality of data/insight
Fewer IT-related bottlenecks
Accelerated development and testing
Strengthened data access governance
Improved training sets for Al/ML models
Facilitated collaboration
Streamlined compliance and legal capabilities
Reduced technology configuration time
Reduced repetitive or redundant efforts
Lowered skills/ training barriers to data use
Other
Data governance initiatives have not added value to my organization
My organization has no data governance initiatives
Source: 451 Research's Voice of the Enterprise: Data & Analytics, Data Management & Analytics 2021
Faster access to relevant data
Higher quality of data/insight
6

© Anonos 2023 |
Despite interdependencies, businesses view privacy and security as barriers
Data privacy and data security are the top reported challenges in getting a more "unified" view of data
54%
43%
30%
26%
26%
26%
25%
25%
24%
24%
23%
19%
17%
16%
15%
<1%
3%
Data privacy requirements
Data security requirements
Variety of data sources
Number of data silos
Legacy architecture or applications
Skills shortage
Multicloud or hybrid architecture
Open source management
Streaming/real-time requirements
Reliance on hand-coding
Volume of data
Lack of executive buy-in
Self-service demand for data
Lack of multi-domain view/mastering
Lack of budget
Other
None of the above
Data privacy requirements
Data security requirements
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© Anonos 2023 |
41.3%
24.6%
11.3%
11.3%
8.5%
0.3%
2.7%
0.0%
IT (general)
Information security
Compliance
Dedicated data privacy team
Risk management
Other (please specify)
No group or function holds primary responsibility for data privacy and data protection
Don't know
IT (general)
Information security
Which group in your organization holds the primary responsibility for
managing data privacy and data protection requirements?
8

© Anonos 2023 |
Point Solutions Don’t Eliminate the Tradeoff Between Data
Protection & Utility
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Data Protection Techniques
Statutory Pseudonymization
Masking
K-Anonymity
Tokenization
Synthetic Data
Cleartext
Homomorphic Encryption (HE)
Trusted Execution Environment (TEE)
Cohorts/Clusters
Generalization
Differential Privacy
Multi-Party Computing (MPC)
Cleartext with Access Controls
Protects Data
in Use
YES
YES
YES
YES
YES
NO
YES
YES
YES
YES
YES
NO
YES
Reconciles Conflicts
Between Protection
and Accuracy
YES
NO
NO
NO
MIXED
NO
Supports
AI and Machine
Learning
YES
YES
YES
NO
YES
NO
NO
YES
NO
YES
Supports Protected
Data Sharing and
Multi-Cloud Processing
YES
NO
YES
YES
YES
YES
YES
YES
YES
YES
YES
Utility
Comparable
to Cleartext
MIXED
MIXED
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© Anonos 2023 |
3
Analytics,
ML and AI
Model
Building
5
Sharing with
Service
Providers
6
Sharing for
Monetization
7
Sharing for
Enrichment
1
Test, Dev
and Demo
Data
2
Internal
Data
Sharing
Data Use Case Maturity Curve
4
Analytics, ML
and AI Model
Deployment
7 Universal Data Use Cases
10
10

© Anonos 2023 |
Privacy Platform Approach
11
Test, Dev and
Demo Data
Analytics, AI/ML
Model Building
Analytics, AI/ML
Model Deployment
Internal
Data Sharing
Sharing with
Service Providers
Sharing for
Monetization
Sharing for
Enrichment
Source Data
1 2 3 4 5 6 7
7 UNIVERSAL DATA USE CASES
Privacy Platform Approach Enables
Integrated Privacy/Security/Governance
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© Anonos 2023 |
OIL
Single-Use Asset
12

© Anonos 2023 |
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ulti-Use
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W
ater
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
WATER
Generative,
Multi-Use Asset
OIL
Single-Use Asset
VS.
13

Panel Discussion
Awah Teh
Vice President of
Data Governance &
Privacy Engineering
Joseph Sommer
Data & Analytics,
Managing Partner
Steve Prestidge
Chief Commercial &
Innovation Officer
WEBINAR
Capital One EY Anonos

© Anonos 2023 |
What do you think about characterizing
Data as the “New Water” versus the “New
Oil”? Do you think approaching privacy,
security & governance as interconnected
functions can help to create generative
data value?
15
1

© Anonos 2023 |
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ater
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ulti-Use
Asset
W
ater
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
Water
Multi-Use Asset
WATER
Generative,
Multi-Use Asset
OIL
Single-Use Asset
VS.
16

© Anonos 2023 |
What are the impediments to enterprises
shifting from data loss prevention to data
value maximization, resilience, and
sustainability? How would these shifts
augment or undermine the path of
current programs?”
18
3

© Anonos 2023 |
What benefits have you seen from
converging data privacy, security, and
governance to treat them as value
centers and from arming them with new
technologies? What benefits do you
think enterprises can realize from
adopting this approach?
19
4

© Anonos 2023 |
With regulatory/legal frameworks
changing to address different aspects
of privacy & security, what can
enterprises do to stay ahead?
20
5

© Anonos 2023 |
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Anonos Data Embassy dynamic de-identification, pseudonymization and anonymization
systems, methods and devices are protected by an intellectual property portfolio that
includes but is not limited to: Patent Nos. CN ZL201880044101.5 (2022); JP 7,064,576
(2022); CA 3,061,638 (2022); AU 2018258656 (2021); US 11,030,341 (2021); EU 3,063,691
– Austria, Belgium, Croatia, France, Germany, Ireland, Italy, Luxembourg, Netherlands,
Switzerland and United Kingdom (2020); CA 2,975,441 (2020); US 10,572,684 (2020); CA
2,929,269 (2019); US 10,043,035 (2018); US 9,619,669 (2017); US 9,361,481 (2016); US
9,129,133 (2015); US 9,087,216 (2015); and US 9,087,215 (2015); plus 70+ additional
domestic and international patent assets. Anonos, Data Embassy, Variant Twin and Data
Without the Drama are trademarks of Anonos Inc., protected by federal and international
statutes and treaties.
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The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Resilience

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