Post on 15-Jul-2015
Many sources
Multiple views of multiple sources is the data challenge
OpenGamma(Postgress)
Reference Data
Corep Finrep(XBRL Taxonomy)
Spreadsheets
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Data warehouse
Front office system
Client ID Name Clienttype
1 Thatcher Gold
2 Blair Silver
3 Cameron Bronze
Risk system
Client ID
LEI Name Clienttype
Risk Rating
1 987 Thatcher Gold High
2 654 Blair Silver Medium
3 654 Cameron Bronze Medium
321 Obama LowLEI Name Risk rating
987 Thatcher High
654 Blair Medium
321 Obama Low
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Warehouse duplicates & transforms the data
ModelDRExisting systems
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Data Point Model architecture
OpenGamma(Postgress)
EBA COREP(Access)
Corep Finrep(XBRL Taxonomy)
Spreadsheets
Data point models
EBA COREP
Spreadsheets
Corep Finrep
FIBO
Open Gamma
In place
access
Sem
anti
cs
View 1
View 2
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View 4
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The Data Point Model
Value Value SetData Point
Aspect
Context
Many
Value
1
The data point meta model separates the data points and their values
And treats concept relationships as data
Traditional strategy
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Example DPM with instance data
DoBs Client
1925-10-13 Thatcher
1953-05-06 Blair
1953-05-06 Cameron
Data Point Model
Aspect Values
1945-01-01
1953-05-06
Aspect Values
Thatcher
Blair
Cameron
DPs
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7f%$
^rrA
FQ!@
~A¬0
Aspects
DoB
Client
Ru
les
Regulator RolesReporting and analytics
Data management tooling
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How ModelDR fits into the banking ecosystem
modelDR
Systems
Trading systems
Calculation Engine
Reg Reportneeds
(e.g. XBRL taxonomy)Spreadsheets
Risk systems
Data warehouses
Report writer
Data modelling
Ontology managementTopbraid
Data Architect
Manager
Data Owner
Standards
FIBO
New viewpoint requirements
Report schema & semantics
Global language
Existing Ontologies
Data Models
RDF & Sparql
Data Schemas
Existing Report Designs
Semi structuredData designs
Inputs &Outputs
Cross DBQueries
New schemas
New Ontologies
New Report Designs
Meta data in SS
Congruent View of 100%
Data quality metrics
Congruent View
• Gives a single, congruent viewpoint of all the banks data (with provenance)
• Enables queries across multiple database, eliminating new data warehouses
• Provides users fingertip access to the data architecture in each system
• Speaks a common business language by integrating financial ontologies like
FIBO and XBRL
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A third DPM wired together from 2
existing DPM
Regulation may be the
driver but efficiencies will
evolve from a universal
language across the big
data technology curveSelect legacy
systems for
ModelDR to
reverse
engineer into
DPM format
ModelDR‘wires up the new DPM viewpoint to an existing or new database
Model DR
forward
engineers
a query
drawn
from the
new
viewpoint
New reports are drawn from old system architecture
Assessment of tactical transition to the ModelDRstrategic solution
Steps towards the Model DR data solution
Use cases with demonstration
1. Untangle existing databases
2. Untangle existing spreadsheets
3. Measure and guarantee data quality
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Business Entity
Class Level Adaptor
Attribute Adaptors
Adaptors Class Level Aspect
Attribute Level Aspect
Attribute LevelValue Sets
Resources
1. Untangle an existing data base
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2: Untangle a spreadsheet
Report NameY Axis Aspect Y Axis Value Set Name Y Axis Coordinate Aspect Values
ReportableAspect
X Axis Aspect
X AxisValue Set
X AxisCoordinateAspect Values
Reportable Aspect Values
Systems
Data management tooling
Reporting and analytics Regulator
Duplication
Coverage
ConsistencyAccuracy
completeness
conformity
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3. Measure and guarantee data quality
Roles
modelDR
Trading systems
Calculation Engine
Reg Reportneeds
(e.g. XBRL taxonomy)Spreadsheets
Risk systems
Data warehouses
Report writer
Data modelling
Ontology management
Data Architect
Business Domain Expert
Data Owner
FIBO
Cross DBDQ Queries
Data quality metrics
Meta data Analysis
Definition of Good
Data QualityReport Designs