7. Context of Operation – delivering tailored financial management by mirroring customer needs in the services we use .
real-time packaging and underwriting of financial service and management
The ecosystems together derive
needs and and translate them in to
offerings
We need to be able to mirror
an individual’s humanity and
ambition in the services that
we use to manage their
financial health.
This requires us to grow a
strong relationship.
8.
9. Context of Operation – making data work for us
we need to be able to mirror personal needs within our tailored services that match our vision making bettering
returns on investment
The ecosystems manage the
Relationship of the customer
With services
Points of convergence – the more overlay we have here the better and timely match for convergence/sale
Our Business
Our Customer
10. Data Harmony
as energy never dies it simply takes different forms, so does data. This is a continuous
model driven by creativity and disruption and tamed by intelligence, knowledge and
operational feedback
Data Relevance 2 Lifecycle
Data Relevance 1 Lifecycle
Data Harmonic Lifecycle
The ecosystems together support
the data harmony models
11. THE AEGON ONE ECO-SYSTEM
MAKING SENSE OF DATA AND TRANSACTIONS & BUILDING TRUST
12. All Eco-System working in Harmony?
They can work singularly or as part of an interoperable suite.
OMNICHANNEL BI PORTAL
DATA IMPORT
DATA EXPORTDATA LAKE
DATA PUBLICATION
DATA LAB
13. THE ONE AEGON ECO-SYSTEM TECHNOLOGIES
1. USE CLOUD SERVICES AS MUCH AS POSSIBLE
2. USE OPEN-SOURCE AS MUCH AS POSSIBLE
3. USE TECHNOLOGY WITH SMALL COMPUTE FOOTPRINTS
4. USE STATELESS MICRO SERVICES (1 Compute : 1 Platform: 1 Task)
1. MOVE AWAY FROM LARGE CLUSTER TECHNOLOGY
2. SEPARATE COMPUTE FROM DATA
3. FIX ON A SINGLE CLOUD, ALLOW FOR INTEROPERATION WITH OTHER CLOUD SERVICES
4. KEEP DATA MOVEMENT TO A MINIMUM, MOVE COMPUTE AND MODELS
14. How do they interoperate ?
The whole is greater than the sum of the parts. But the parts
themselves are also very special
15. Data LAKE
Production Data & Meta Models
Production,
Business Data
Cold Storage
AI, ML – Neural Net (DLb) Taxanomic Processing *
Meta Model Search &
Data Publication
THE DATA LAKE ECOSYSTEM (DLk)
* this is Blooms taxonomy model
Data Exhausting
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
16. THE DATA LAKE ECOSYSTEM (DLk)
DOMAINS WITHIN THE DATA LAKE ECOSYSTEM
17. THE DATA LAKE ECOSYSTEM (DLk)
ENGINEERING SCHEMATIC
[DATA LAKE]
18. TOP 10 CAPABILITIES OF THE DATA LAKE ECOSYSTEM
1. SECURE PRODUCTION DATA ON THE CLOUD
2. REGULATORY & SOVEREIGNTY GOVERNANCE AND COMPLIANCE BUILT-IN
3. VISIBILITY ON ALL PRODUCTION DATA CLASSES, QUALITY, COMPLETENESS AND LIFCYCLE
4. PUBLISH UP TO DATE & HISTORIC PRODUCTION DATA & ITS META MODELS ADHERING TO GOVERNABLE DATA CONTROLS
5. ANSWER ALL QUESTIONS ON PRODUCTION DATA USING SEMANTIC AI/ML WITHOUT HAVING TO ACCESS THE DATA
6. CREATION OF NEW DATA DICTIONARIES FOR DIGITAL ONLY WITHOUT DIRTYING CORE INDUSTRY DATA MODELS
7. SUPPORT DATA FEDERATION AT A LOCAL, COUNRTY, CONTINENT AND GLOBAL LEVEL.
8. ON THE CLOUD BUT INVISIBLE TO THE OUTSIDE WORLD
9. SINGLE POINT OF HUMAN ACCESS WITH SECURITY EXTRECATED FROM CLOUD SECURITY
10. FULLY AUDITABLE, MONITORED AND ALTERTED AT ANY LEVEL OF GRANULARITY LOCALLY AND GLOBALLY
19. Data Pub
Published Data & Meta Models(DP)
Data Exhausting
AI, ML – Neural Net (DLb) Taxanomic Processing *
Meta Model Search &
Data Publication
THE DATA PUBLICATION ECOSYSTEM (DP)
* this is Blooms taxonomy model
Production Data &
Meta Models (DLk)
Cold Storage
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
20. THE DATA PUBLICATION ECOSYSTEM (DP)
DOMAINS WITHIN THE DATA PUBLICATION ECOSYSTEM
21. TOP 10 CAPABILITIES OF THE DATA PUBLICATION ECOSYSTEM
1. ACCESS TO MASSIVELY SCALABLE SECURED FIT-FOR-PURPOSE PRODUCTION DATA.
2. SUPPORT ANY DATA TECHNOLOGY WITHOUT HAVE TO WORRY ABOUT TECHNOLOGY SCHEMAS.
3. CREATE, REFRESH AND REMOVE DATA WITHOUT ANY ADVERSE AFFECTS TO DOWNSTREAM OR CROSSSTREAM FUNCTIONS
4. IMPORT DATA FROM EXTERNAL SOURCES SECURELY FOR FUNCTIONAL POINT OPERATIONAL REQUIREMENTS
5. CAN SUPPORT ALL OPERATIONAL ACCESS NEEDS - TEST, DEV, PRODUCTION – REDUCING REQUIRED ENVIRONMENTS
6. SECURE MULTITENANCY ACCESS TO DATA WITH NO FEAR FOR CROSS POLLINATION OR DATA LEAKAGE
7. SUPPORT DATA FEDERATION AT A LOCAL, COUNRTY, CONTINENT AND GLOBAL LEVEL.
8. ON THE CLOUD BUT INVISIBLE TO THE OUTSIDE WORLD
9. SINGLE POINT OF HUMAN ACCESS WITH SECURITY EXTRECATED FROM CLOUD SECURITY
10. FULLY AUDITABLE, MONITORED AND ALTERTED AT ANY LEVEL OF GRANULARITY LOCALLY AND GLOBALLY
22. Deployment architecture
Data LAB
BI REPORTS
Data Sets Creation
Analytics, Cubes, AI, ML, BOTS, Neural Nets Cells
Public, Social ,
Market Data & IoT
Data Exhausting
Taxanomic Data Science. AI ML Creation, Packaging
THE DATA LAB ECOSYSTEM (DLb)
Publication
Data Sets (DP)
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
23. THE DATA LAB ECOSYSTEM (DLb)
DOMAINS WITHIN THE DATA LAB ECOSYSTEM
25. TOP 10 CAPABILITIES OF THE DATA LAB ECOSYSTEM
1. UNBOUNDED CREATIVE LAB FOR ALL THINGS DATA, AI, ML, ANALYTICS, INTELLIGENCE AND KNOWLEDGE.
2. NO NEED TO MOVE DATA OUT OF CLOUD TO EXECUTE MASSIVE COMPUTE AGAINST MASSIVE DATA
3. PACKAGE INTELLIGENCE, KNOWLEDGE AI, ML, INSIGHTS FOR USE WITHIN BUSINESS PROCESS AND OPERATION DASHBOARDS
4. GROW INTELLIGENCE FOR BOTS, BIOMETRIC IDENTITIES, FRAUD PREVENTION, TRUST EVALUATION
5. CAN SUPPORT ALL OPERATIONAL ACCESS NEEDS - TEST, DEV, PRODUCTION – REDUCING REQUIRED ENVIRONMENTS
6. SECURE MULTITENANCY ACCESS TO DATA WITH NO FEAR FOR CROSS POLLINATION OR DATA LEAKAGE
7. SUPPORT DATA FEDERATION AT A LOCAL, COUNRTY, CONTINENT AND GLOBAL LEVEL.
8. ON THE CLOUD BUT INVISIBLE TO THE OUTSIDE WORLD
9. SINGLE POINT OF HUMAN ACCESS WITH SECURITY EXTRECATED FROM CLOUD SECURITY
10. FULLY AUDITABLE, MONITORED AND ALTERTED AT ANY LEVEL OF GRANULARITY LOCALLY AND GLOBALLY
26. Deployment architecture
BI Reporting
BI REPORTS
Data Sets Creation (DLb)
Analytics, Cubes, AI, ML, Neural Nets Cells
Public, Social ,
Market Data & IoT
Data Exhausting
Data Science. AI ML Creation and Packaging
Publication
Data Sets (DP)
THE BI PORTAL ECOSYSTEM (BI)
BI REPORTS
BI DASHBOARDS
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
27. THE BI PORTAL ECOSYSTEM (BI)
DOMAINS WITHIN THE BI PORTAL ECOSYSTEM
29. TOP 10 CAPABILITIES OF THE BI PORTAL ECOSYSTEM
1. BOUNDED PORTAL TO DELIVER DASHBOARD AND REPORTS ACROSS ALL MEDIUMS AND ASSOCIATED DEVICES
2. NO NEED TO MOVE DATA OUT OF CLOUD TO SUPPORT ACCESS AT SCALE
3. PACKAGE REPORTING DATA FROM EXTERNAL SOURCE – REGULATORS, PARTNERS, SHAREHOLDERS, CUSTOMERS
4. REPORT AND REALTIME CHANGES BASED ON BOTH INTERNAL, EXTERNAL AND BLENDED INSIGHTS
5. CAN SUPPORT ALL OPERATIONAL ACCESS NEEDS - TEST, DEV, PRODUCTION – REDUCING REQUIRED ENVIRONMENTS
6. SECURE MULTITENANCY ACCESS TO DATA WITH NO FEAR FOR CROSS POLLINATION OR DATA LEAKAGE
7. SUPPORT DATA FEDERATION AT A LOCAL, COUNRTY, CONTINENT AND GLOBAL LEVEL.
8. ON THE CLOUD BUT INVISIBLE TO THE OUTSIDE WORLD
9. SINGLE POINT OF HUMAN ACCESS WITH SECURITY EXTRECATED FROM CLOUD SECURITY
10. FULLY AUDITABLE, MONITORED AND ALTERTED AT ANY LEVEL OF GRANULARITY LOCALLY AND GLOBALLY
30. Deployment architecture
BI REPORTS
Data Sets Creation (DLb)
AI, ML, Neural Nets Cells (DLb)
Public, Social ,
Market Data & IoT
Production Writes/Alerts
Data Science. AI ML Creation and Packaging
Publication
Data Sets (DP)
THE OMNICHANNEL ECOSYSTEM (OC)
Customer, Business, Bots & API Interactions
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
32. THE DATA EXPORT Hub ECOSYSTEM (DEh)
* this is Blooms taxonomy model
Production Data &
Meta Models (DLk/b)
Partners & Regulators
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
33. THE DATA EXPORT Hub ECOSYSTEM (DEh)
DOMAINS WITHIN THE DATA EXPORT ECOSYSTEM
35. TOP 10 CAPABILITIES OF THE DATA EXPORT ECOSYSTEM
1. PACKAGES DATA FOR EXPORT UNDER STRICT GOVERNANCE AND DATA CONTROLS
2. SUPPORTS ALL EXTERNAL DATA INTEGRATIONS AND INTERPORATIONAL PROTOCOLS AND SECURITY
3. SUPPORTS ACCESS WINDOWS TO ENSURE TIGHTER LEVEL OF SECURITY ON VISIBLE ACCESS POINTS
4. PROVIDES OPEN API SECURED FOR A MORE RELAXED PARTNER ACCESS TO DATA
5. SUPPORTS ALL DATA TYPES ACROSS THE ECOSYSTEM TOPOLOGY AND ALL DATA FORMATS
6. CAN SUPPORT ALL OPERATIONAL ACCESS NEEDS - TEST, DEV, PRODUCTION – REDUCING REQUIRED ENVIRONMENTS
7. SECURE MULTITENANCY ACCESS TO DATA WITH NO FEAR FOR CROSS POLLINATION OR DATA LEAKAGE
8. SUPPORT DATA FEDERATION AND SERVICE COMBINATION AT A LOCAL, COUNRTY, CONTINENT AND GLOBAL LEVEL.
9. SINGLE POINT OF HUMAN ACCESS WITH SECURITY EXTRECATED FROM CLOUD SECURITY
10. FULLY AUDITABLE, MONITORED AND ALTERTED AT ANY LEVEL OF GRANULARITY LOCALLY AND GLOBALLY
36. THE DATA IMPORT Hub ECOSYSTEM (DIh)
* this is Blooms taxonomy model
Production Data &
Meta Models (DLk/b)
Partners & Regulators
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
37. THE DATA IMPORT Hub ECOSYSTEM (DIh)
DOMAINS WITHIN THE DATA IMPORT ECOSYSTEM
39. TOP 10 CAPABILITIES OF THE DATA IMPORT ECOSYSTEM
1. IMPORTS DATA FROM EXTERNAL SOURCES AND PARTNERS UNDER STRICT GOVERNANCE AND DATA CONTROL
2. SUPPORTS ALL EXTERNAL DATA INTEGRATIONS AND INTERPORATIONAL PROTOCOLS AND SECURITY
3. SUPPORTS VIRUS AND MALWARE PROTECTION ON ACROSS ALL IMPORTS AND HEADER ANALYSIS
4. PROVIDES OPEN API SECURED FOR A MORE RELAXED PARTNER DEPLOYMENT OF DATA
5. SUPPORTS ALL DATA TYPES AND APPORPRIATE TRANSFORMATIONS
6. CAN SUPPORT ALL OPERATIONAL ACCESS NEEDS - TEST, DEV, PRODUCTION – REDUCING REQUIRED ENVIRONMENTS
7. SECURE MULTITENANCY ACCESS TO DATA WITH NO FEAR FOR CROSS POLLINATION OR DATA LEAKAGE
8. SUPPORT DATA FEDERATION AND SERVICE COMBINATION AT A LOCAL, COUNRTY, CONTINENT AND GLOBAL LEVEL.
9. SINGLE POINT OF HUMAN ACCESS WITH SECURITY EXTRECATED FROM CLOUD SECURITY
10. FULLY AUDITABLE, MONITORED AND ALTERTED AT ANY LEVEL OF GRANULARITY LOCALLY AND GLOBALLY
40. DELIVERY OF GLOBAL DATA, INSIGHTS, INTELLIGENCE
ONE AEGON
BIG DATA ON A GLOBAL SCALE
GLOBAL INTELLIGENCE CREATION
LOCAL INTELLIGENT EXECUTION
MOVE ALGORITHM AND MODELS
NOT DATA AND COMPUTE
41. WE HAVE ALREADY STARTED ON TOMORROWS JOURNEY?
% of Completion for fully working operational eco-suite.
55% 35%
35%50%20%
10%3%
The dev to date is driven through JIT
Dev based on business need
NOTE.
Each Eco-system can exist
on its own or any part of
this configuration as a suite.
42.
43. Current Deployments
User Usage
Type
Data Lake Data Lab Data Exp Data Imp BI Portal Data Pub Omni
Channel
KNAB PROD * * * * * *
AAM POC * * *
AEGON
LIFE
POC * *
NL POC * *
SPAIN POC * * * * * *
OPERATIONAL AREAS COVERED
BANKING, INSURANCE, ASSETMANAGEMENT – ONE FABRIC – MANY SOLUTIONS – ONE ECOSYSTEM