Le dimensioni del Gruppo UniCredit HVB La gestione delle

GOVERNARE LA COMPLESSITÀ
DELL’INFORMAZIONE STRUTTURATA
IN UN’AZIENDA BANCARIA APERTA
“Whatever you can do,
or dream you can do, begin it.
Boldness carries genius,
power, and magic.”
(Goethe)
30 Gennaio 2007
ABSTRACT
Le dimensioni del Gruppo UniCredit HVB
La gestione delle informazioni strutturate
Data warehouse environment
Il modello dei dati
Gli users
Meta warehouse environment
L’xml come linguaggio sintattico
Metadata management
Gli stakeholders
Il portale dei metadati
La nostra mission
Il mondo della ricerca
2
1
UNICREDIT IS THE FIRST TRULY EUROPEAN BANK …
Banking operations in
19 countries
28 million customers
7,184 branches
148,000 employees
Net Profit: € 3,4 bn1
Total Assets: € 782 bn
Deposits and debt
certificates: € 462 bn
Loans: € 427 bn
Global player in Asset
Management: approx.
€ 272 bn AuM with
coverage in 20
countries in 5
continents
25th European
company in terms of
capitalization2
Thinking globally
and operating on
multi-local basis
Creating
sustainable
long-term value
Exploiting
complementary
nature of Group's
best practices
Developing the
best of local
cultures and
brands already
recognized and
established
3
Note: 2005 data
1
Consolidated 2005 pro forma for UCI Group including HVB Group stand alone 12 months results, integration effects and other one-off costs
2
Ranking as at 16 march 2006 - Source: Datastream
… WITH AN EXTENSIVE GEOGRAPHICAL PRESENCE …
UniCredit
Oslo
Bank Pekao+ BPH
Amsterdam
Lussemburgo
Luxembourg
HVB Lithuania
HVB Latvia
HVB Estonia
International
Moscow Bank + Yapi Moscow
Pekao Ukraine + HVB Ukraine
Bank
Zivnovstenska HVB Czech
+ Republic
Banka
HypoVereinsbak
Brussels
UniBbanka + HVB Slovakia
Dublin
Bank Austria Creditanstalt
London
HVB Hungary
Paris
UniCredit + HVB + Ion Tiriac
Romania Romania Bank
Geneva
Bern
Zurich
BACA Slovenia
Zagrebacka + Splitska Banka
Banka
UniCredit
HVB Central
Zagrebacka +
Profit B.
Monaco
Madrid
HVB Serbia + Eksimbanka
San Marino
Koc Bank Azerbaijan
Skopje
Bulbank + HVB + Hebros
Biokim
Bank
Athens
Atene
Koc Bank + Yapi Kredi
Seoul
Tokyo
Hong Kong
Beijing
Shanghai
Guangzhou
Hanoi
Singapore
New York
Boston
Miami
Mexico City
Mumbai
Cairo
Rio de Janeiro
São Paulo
Sydney
Teheran
Tel Aviv
Abu Dhabi
Buenos Aires
Johannesburg
Bahrain
4
Countries where the Group operates via its own branches, representative offices, small banking subsidiaries, or investment centers (Pioneer)
Countries where the Group operates via local banks controlled or in which it has a significant equity interest
2
DATA WAREHOUSE ENVIRONMENT
Legal Entity
Front End
UGIS’s Back End
L
e
g
a
c
y
mainframe
S
t
a
g
i
n
g
AIX
source data
P
r
o
d
u
c
t
i
o
n
D
e
v
e
l
o
p
Planning &
Management
Control
AIX 5.2 +UDB 8.2
C.R.M.
8 TBTB-5 Data Base
22.000 tables
AIX 5.3 +UDB 8.2
D
e
l
i
v
e
r
y
datamarts
cubes
11°level
° level data
22°level
° level data
33°level
° level data
5
DATA WAREHOUSE - DATA MODEL
(EXEMPLES OF A SUBJECT AREA – CUSTOMER DATABASE)
6
3
DATA WAREHOUSE USERS
Users (up to now 1,886) are registered starting from a request of the bank/company using a defined
process of authorization.
Users can be inserted in various groups
Each group has different access to data (read only)
Commercial Banks
Unicredit Banca
Unicredit Banca d'Impresa
Unicredit Private Banking
979
Other Companies
632
505
UniAudit
101
235
Clarima
38
Security Services
11
UB per la Casa
44
UBM
15
148
Zivnostenska Banka
26
CR Fossano
2
CR Rimini
UGC
63
UGIS
8
UniCredit Assicura
275
17
UniCredit
201
UPA
170
URE
1
Xelion
26
7
METADATA WAREHOUSE ENVIRONMENT
UGIS’s EIF
Works decoupled from any hardware
and software platforms
Manages
informations
multilinguage patterns
Supports any type of
originated
in
the
Intelligence environment
in
metadata
Business
Builded to be incremented day by day
Handled without manual processes
Legal entity front end
Warehouse
Model
Dashboards
ODS
Model (*)
Data Mart
Model (*)
Business
Model
MetaData Portal
Meta
Model
Central
metadata
repository
Query &
Reporting
OLAP
Analysis
ETL
Model
BPM Analisys
8
4
METADATA MANAGEMENT - XML IS MAGIC
Central metadata
repository
Central
metadata
repository
9
DATAWAREHOUSE ARCHITECTURE - METADATA
Available technical and business metadata:
Physical properties
Primary & foreign keys, indexes
Availability & cardinality
Users access granting
Business descriptions of entities and attributes
Valid values
Refresh timing & type
…..
Metadata are based on a structured E/R model and managed in a specific
environment (MME).
Users can browse metadata through a multi language intranet portal (EIF Portal).
Next step: availability of operational metadata (w.i.p.).
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5
METADATA MANAGEMENT
CA ERwin
IBM DB2
UDB v8.2
EIF Tools
IBM DB2
os/390
IBM WebSphere
I.I. Datastage
EMC2
Web Publisher
Ownership & Authorization Metadata
instance / language / partitioning / ownership
MetadataWarehouse
business
metadata
Documentation
Bulletin Board
technical metadata
Host System
Flat Files
Tables
business
metadata
transformation
ERwin
Trasformations
technical /operational
metadata
metadata
Logs
Catalogs
ETL process
Mixed process
Online I/O process
Analyst process
11
WAREHOUSE METAMODEL: THE ARCHITECTURE
Analysts
Legenda:
In
te
ra
Scheduler
Intranet End Users
ct
iv
e
Export
Action
X-Frame
de
fin
i
tio
1. Analysis phase
n
2. Data capture phase
3. Metamodel update
ETL
AIX
4. Pure ETL phase
Metamodel
5. Reporting phase
(UDB)
XML
Scheduled UNIX shell
AIX
UNIX shell
ETL Websphere Datastage EE 7.5
End Users
12
6
DATA AND METADATA STAKEHOLDERS
Users’s
Users’sQuery&Reporting
Query&Reporting
(Business
(BusinessDivisions
DivisionsHeadquarters
Headquartersand
andP&C
P&CUnits
Units) )
Application
Applicationsupport
supportservices
services
(Monitoring&Reporting;
(Monitoring&Reporting;C.R.M.;
C.R.M.;Call
CallCenter;
Center;Audit
Auditprocesses)
processes)
DW
1.800 Users
(approximately )
Retail
Division
Corporates/SMEs
Division
Privat Banking & Central Eastern Europe
Asset Management Division
Division
13
METADATA PORTAL: DIFFERT TYPES OF INFORMATION
structured information
14
unstructured information
7
METADATA PORTAL: SUBJECTAREAS
Types of subjectarea
• procedural
• functional
• business
Types of model
• relational
• dimensional
• flat
15
USEFULNESS OF THE METADATA
balance account
Data
das Kontoguthaben Warehouse
Metadata
Warehouse
saldo contabile
saldo contabile
Metadata
DB2
Unicode
balance account
Księgowość
Business
Community
saldo contabile
Kontoguthaben
Legacy Layer
Data
IT Community
Legenda:
:table
:view
:detail
:write
:read
16
8
OUR BELIEF
MetaData Portal
enable local integration
and interoperability
(CRM mapped on DW, e.g.)
promote global integration
we operate locally but think globally
(Zivnostenska Bank’s
reporting, e.g.)
17
UNO SGUARDO ALLA COMUNITÀ SCIENTIFICA: L’INTEGRAZIONE SEMANTICA
Integrazione federata dei dati
Query
Answer (Q)
M1
M2
Integrazione SEMANTICA dei dati
M3
Query
Answer (Q)
Global schema
C2
Ontologia
C1
Wrapping
S1
S2
S3
C3
Source
Mapping
M1
M2
M3
Global schema
Wrapping
S1
S2
S3
Source
Una ontologia è una specifica formale di una concettualizzazione di un
dominio, che rende esplicito il significato dei concetti rilevanti nel dominio.
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9
UNO SGUARDO ALLA COMUNITÀ SCIENTIFICA: L’INTEGRAZIONE SEMANTICA
M1
S1
M2
S2
M3
S3
C2
La banca polocca “chiude”
contabilmente
ogni
sera
pertanto non esiste il dato
“Saldo Liquido” (SAL_LIQ)
Select * from S2 inner join S3 on
S1.SAL_LIQ = S3.SAL_LIQ ...
Business
issue
CFO: voglio il
saldo liquido
della azienda
Rossi Spa
C1
C3
M1
M2
M3
S1
S2
S3
Error
Supponiamo che Rossi spa
abbia cc sia in Italia (S2) sia in
Polonia (S3).
Supponiamo anche C sia il
dominio ontologico dei dati di cc
e che C3 implichi logicamente
C1 (linea tratteggiata ad
esempio: Saldo Liquido implica
Księgowość).
Query sintattica
Query semantica
...
(Saldo liquido) Księgowość
(retrive
[(Saldo Liquido (IT,y) Saldo
Contabile (PL,y)]
...
^
OK
19
Fine della presentazione
Giorgio Barbetta
[email protected]
cell. +39335496359
10