Tim scottkoenverheyenpresentation

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The central information provision layer within Argenta is the name for the central data hub, based on near real time Data Vault, which on one hand answers the information needs of the bank but also feeds applications such as MIFID. This layer is also the base from which the data governance is enforced. For this purpose they use Oracle Enterprise Metadata Manager and Collibra.

Technologie

Data Hub for the financial market
Case: Argenta implements new data warehouse
Koen Verheyen and Tim Scott
17 October 2019

Agenda
1. Introduction and context
2. Programme approach
3. Architecture
4. Technical background
5. Closing + Q&A

5
Argenta
1,72 mio
customers
in Belgium and
the Netherlands
29,8 bn
€ in loans to families
and individuals in
Belgium and the
Netherlands
467
branch offices
in Belgium
2.575
collaborators in
Belgium,
Netherlands
and Luxemburg

Necessity for a data driven organisation has a triple origin
• Customer focus is key for Argenta
• Increasing amount of data to be processed
• Augmented reporting pressure from the various regulators
Programme launched to implement data management and a new data
warehouse (CIVL) using market standard methodology and technology
 Esperanto
6
Argenta context of the Esperanto programme

• Data management
• Fully in line with DAMA-DMBOK principles (11 principles)
• Introducing data stewardship in the business organisation as a central role
• New data warehouse
• DataVault 2.0
• Oracle technology as a platform
• Collibra and OEMM to support data lineage and data documentation
• Galvanize as centralised data quality tool
• Result: standardized and automated company wide data
management for both business as IT
• Single purpose: generate value for the organisation
7
Data management at Argenta

Esperanto
10
High-level operation
CIVL
Logical Info.Model
Business Glossary
B
U
S
I
T
DAO
Data
stewards
CC D&A
CIVL + DWH
R
D
V
B
D
V
P
L
DWH
SAFe4.6
Through the data stewards’ operation
• Logical information model
• Business Glossary
• Data definition
• Data quality rules
• Business Rules
• Logical source mapping
Other projects or
programmes
Reporting or
data need
Throught the IT Data & Analytics operation
• DV modelling
• PL modelling
• Source connectivity
• Model implementation + DQ rules
• Testing
• Release management
S
O
U
R
C
E
S

12
Data management = Tools, processes and people

Issue : Architectuur - As is
13
Output
Boekhouding Model
Wet en Regelgeving
Model
Commercieel Model
Solvency II
Rapportering
Basle II
Rapportering
Overeenkomst
Persoon
Transactie
Profiel
Inzichten
Management
Rapportering
Finance Model
Wettelijke
Rapportering
Client beeld model
Input
Risk Monitoring
Model
Klanten Service Model
Client
Hoedanigheid
Produkt
Zekerheid
Voorwerp
Waardering
Gebeurtenis
Risico meting Model
Interactie
Klant
Regel
Gevers
FMP
WERA
GDPR
MIFID II
METRO
DIM
BCBS 239
KYC

14
Target technical architectuur of CIVL

Based on Data Integration Concepts
15
• Data Warehouse Automation
• The Data Warehouse Institute defines data warehouse
automation as "using technology to gain efficiencies and
improve effectiveness in data warehousing processes. Data
warehouse automation is much more than simply
automating the development process.
It encompasses all of the core processes of data
warehousing including design, development, testing,
deployment, operations, impact analysis, and change
management.”
• Data Warehouse Automation & Data Vault 2.0
• Perfect combination to deliver Business Value.
• Faster Time to Market
• Supports Agile Business
• Higher Quality
• Reduce Risk (Testing not required - proven logic)
• Reduce Cost ( -40% based on existing customers)

Based on Data Integration Concepts
16
• Raw Data Vault = IT-project
• Integrate Source by Source (Technical Track)
• Source Analysis required.
• Only choose functional relevant tables.
• Build integrated “Data Lake” of your structured
Data.
• Business Data Vault - Presentation Layer - Access
Layer = Business-project
• Based on Functional Requirements.
• Business Data Vault
• Information Management Office (Business)
delivers conceptual models that get
translated to DV 2.0 models
• Bridges & Pits for Virtualisation of the
Presentation Layer

Technical background
Extra slides to be confirmed
17

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