ModelDRthe tool that untangles complex information

Many sources

Multiple views of multiple sources is the data challenge

OpenGamma(Postgress)

Reference Data

Corep Finrep(XBRL Taxonomy)

Spreadsheets

View 1

View 2

View 3

View 4

2

Traditional data architecture uses data warehouse

3

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

4

Warehouse duplicates & transforms the data

ModelDRExisting systems

5

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

View 3

View 4

6

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

7

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

!6#^

7f%$

^rrA

FQ!@

~A¬0

Aspects

DoB

Client

Ru

les

Regulator RolesReporting and analytics

Data management tooling

8

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

9

10

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

11

12

Business Entity

Class Level Adaptor

Attribute Adaptors

Adaptors Class Level Aspect

Attribute Level Aspect

Attribute LevelValue Sets

Resources

1. Untangle an existing data base

13

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

14

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