SlideShare una empresa de Scribd logo
1 de 13
Bay4all – über alle Touchpoints dem Kunden
ein positives Service-Erlebnis vermitteln
25.6.2015
Thomas Wolf
Den Touchpoint wählt der Kunde nach Belieben
Information
Vertrags-
abschluss
Vertrag zur
Laufzeit
Folgevertrag Kündigung
Post
Gespräch
PC/Internet
Call-Center
… auch den Zeitpunkt wählt der Kunde nach
Belieben
… und dann bitte sofort verfügbar sein
Nach der Arbeit
Früh am Morgen
Während die Kinder schlafen
… deshalb sind alle Touchpoints immer aktiv
… aber was bedeutet das für die Datenbasis?
konsistent
ganzheitlich
aktuell
keine Wartezeiten
immer verfügbar
… SOLL
Akquisedate
n
… IST
Die Bayerische wurde 1858 gegründet
- Datenhistorie
- Migrationshistorie
mehrere unterschiedlich „alte“ Bestandssysteme
- Daten sind nicht widerspruchsfrei
- unterschiedlich aktuell
- unterschiedliche Downzeiten
… LÖSUNG
Bay4all
Replikation
Host
Verträge Sach
Verträge Leben
Kunden
…
Bestandssysteme verwenden zum Teil das VAA-
Model
msg.PM
VAA-Model
=
…
Verträge Sach
Verträge Leben
Kunden
Bestandssysteme
Replikation
Einspielen der Replikationsnachrichten
lesen, speichern, navigieren
nodes, relations, properties
Neo4J
P
M
Transformation
Basis Mapping
Transaction Event Handler
Label Indexer
Nachricht im PM-Message Format
P
M
PM-Message im Graphen-Format
Zusammenfassung (Properties z.B. zu
Vertrag)
einzelne Properties
kombinierte Properties
Data
Store
Lucene
Indexe
exaktes Suchen, kombinierte Suche
Keys, node-Adressen
m
Vorname m/wName node-Adresse
w
Auer
Zöller
Karl
Eva
81517
58999
node-AdresseVertragsnummer
0000001
9990000
23114
44539
node-AdresseName
Auer
Zöller
81517
58999
Mechanismen der Bestandsdatenreplikation
…
Verträge Sach
Verträge Leben
Kunden
Bestandssysteme
Gesamtbefüllung
Änderungsnachrichten
schwebende Änderungen
Bestands-Services auf EINER Graphdatenbank
fachliche Aufbereitung und Darstellung
Erzeugen, Lesen, Ändern, Löschen
Neo4j: nach einem Jahr in Produktion
 fast komplett generische Entkopplung vom HOST
 performant
 professioneller Support durch Partnerschaft mit neotechnology
 keine Downzeiten
 eine zentrale Datenbasis für alle Kundentouchpoints
1 bis 2 Stunden für Gesamtbefüllung bei 1 Mio Verträgen
max. 1 bis 2 Sekunden für Suchen
 ganzheitlich, widerspruchsfrei, aktuell, immer verfügbar

Más contenido relacionado

Destacado

Graph all the things
Graph all the thingsGraph all the things
Graph all the thingsNeo4j
 
Graph Search and Discovery for your Dark Data
Graph Search and Discovery for your Dark DataGraph Search and Discovery for your Dark Data
Graph Search and Discovery for your Dark DataNeo4j
 
GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2
GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2
GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2Neo4j
 
GraphDay Noble/Coolio
GraphDay Noble/CoolioGraphDay Noble/Coolio
GraphDay Noble/CoolioNeo4j
 
Meetup Analytics with R and Neo4j
Meetup Analytics with R and Neo4jMeetup Analytics with R and Neo4j
Meetup Analytics with R and Neo4jNeo4j
 
Graphs fun vjug2
Graphs fun vjug2Graphs fun vjug2
Graphs fun vjug2Neo4j
 
GraphTalk - Semantische Netze mit structr
GraphTalk - Semantische Netze mit structrGraphTalk - Semantische Netze mit structr
GraphTalk - Semantische Netze mit structrNeo4j
 
GraphTalk Frankfurt - Einführung in Graphdatenbanken
GraphTalk Frankfurt - Einführung in GraphdatenbankenGraphTalk Frankfurt - Einführung in Graphdatenbanken
GraphTalk Frankfurt - Einführung in GraphdatenbankenNeo4j
 
Graph all the things - PRathle
Graph all the things - PRathleGraph all the things - PRathle
Graph all the things - PRathleNeo4j
 
GraphTalks - Einführung
GraphTalks - EinführungGraphTalks - Einführung
GraphTalks - EinführungNeo4j
 
GraphTalk - Semantisches PDM bei Schleich
GraphTalk - Semantisches PDM bei Schleich GraphTalk - Semantisches PDM bei Schleich
GraphTalk - Semantisches PDM bei Schleich Neo4j
 
RDBMS to Graphs
RDBMS to GraphsRDBMS to Graphs
RDBMS to GraphsNeo4j
 
Neo4j Makes Graphs Easy: Nicole White
Neo4j Makes Graphs Easy: Nicole WhiteNeo4j Makes Graphs Easy: Nicole White
Neo4j Makes Graphs Easy: Nicole WhiteNeo4j
 
GraphConnect 2014 SF: Graphing the Supply Chain
GraphConnect 2014 SF: Graphing the Supply ChainGraphConnect 2014 SF: Graphing the Supply Chain
GraphConnect 2014 SF: Graphing the Supply ChainNeo4j
 
Introduction to graph databases GraphDays
Introduction to graph databases  GraphDaysIntroduction to graph databases  GraphDays
Introduction to graph databases GraphDaysNeo4j
 
GraphDay Stockholm - Fraud Prevention
GraphDay Stockholm - Fraud PreventionGraphDay Stockholm - Fraud Prevention
GraphDay Stockholm - Fraud PreventionNeo4j
 
Using Neo4j from Java
Using Neo4j from JavaUsing Neo4j from Java
Using Neo4j from JavaNeo4j
 
Introduction to Neo4j and .Net
Introduction to Neo4j and .NetIntroduction to Neo4j and .Net
Introduction to Neo4j and .NetNeo4j
 
Initiation à Neo4j
Initiation à Neo4jInitiation à Neo4j
Initiation à Neo4jNeo4j
 
Introduction: Relational to Graphs
Introduction: Relational to GraphsIntroduction: Relational to Graphs
Introduction: Relational to GraphsNeo4j
 

Destacado (20)

Graph all the things
Graph all the thingsGraph all the things
Graph all the things
 
Graph Search and Discovery for your Dark Data
Graph Search and Discovery for your Dark DataGraph Search and Discovery for your Dark Data
Graph Search and Discovery for your Dark Data
 
GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2
GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2
GraphConnect 2014 SF: Betting the Company on a Graph Database - Part 2
 
GraphDay Noble/Coolio
GraphDay Noble/CoolioGraphDay Noble/Coolio
GraphDay Noble/Coolio
 
Meetup Analytics with R and Neo4j
Meetup Analytics with R and Neo4jMeetup Analytics with R and Neo4j
Meetup Analytics with R and Neo4j
 
Graphs fun vjug2
Graphs fun vjug2Graphs fun vjug2
Graphs fun vjug2
 
GraphTalk - Semantische Netze mit structr
GraphTalk - Semantische Netze mit structrGraphTalk - Semantische Netze mit structr
GraphTalk - Semantische Netze mit structr
 
GraphTalk Frankfurt - Einführung in Graphdatenbanken
GraphTalk Frankfurt - Einführung in GraphdatenbankenGraphTalk Frankfurt - Einführung in Graphdatenbanken
GraphTalk Frankfurt - Einführung in Graphdatenbanken
 
Graph all the things - PRathle
Graph all the things - PRathleGraph all the things - PRathle
Graph all the things - PRathle
 
GraphTalks - Einführung
GraphTalks - EinführungGraphTalks - Einführung
GraphTalks - Einführung
 
GraphTalk - Semantisches PDM bei Schleich
GraphTalk - Semantisches PDM bei Schleich GraphTalk - Semantisches PDM bei Schleich
GraphTalk - Semantisches PDM bei Schleich
 
RDBMS to Graphs
RDBMS to GraphsRDBMS to Graphs
RDBMS to Graphs
 
Neo4j Makes Graphs Easy: Nicole White
Neo4j Makes Graphs Easy: Nicole WhiteNeo4j Makes Graphs Easy: Nicole White
Neo4j Makes Graphs Easy: Nicole White
 
GraphConnect 2014 SF: Graphing the Supply Chain
GraphConnect 2014 SF: Graphing the Supply ChainGraphConnect 2014 SF: Graphing the Supply Chain
GraphConnect 2014 SF: Graphing the Supply Chain
 
Introduction to graph databases GraphDays
Introduction to graph databases  GraphDaysIntroduction to graph databases  GraphDays
Introduction to graph databases GraphDays
 
GraphDay Stockholm - Fraud Prevention
GraphDay Stockholm - Fraud PreventionGraphDay Stockholm - Fraud Prevention
GraphDay Stockholm - Fraud Prevention
 
Using Neo4j from Java
Using Neo4j from JavaUsing Neo4j from Java
Using Neo4j from Java
 
Introduction to Neo4j and .Net
Introduction to Neo4j and .NetIntroduction to Neo4j and .Net
Introduction to Neo4j and .Net
 
Initiation à Neo4j
Initiation à Neo4jInitiation à Neo4j
Initiation à Neo4j
 
Introduction: Relational to Graphs
Introduction: Relational to GraphsIntroduction: Relational to Graphs
Introduction: Relational to Graphs
 

Más de Neo4j

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansQIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansNeo4j
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityNeo4j
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Neo4j
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfNeo4j
 
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...Neo4j
 
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosBBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosNeo4j
 
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Neo4j
 
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jGraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jNeo4j
 
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j
 
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfRabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j
 
Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Neo4j
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeNeo4j
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsNeo4j
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j
 
Neo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j
 

Más de Neo4j (20)

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and BioinformaticiansQIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
QIAGEN: Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
 
EY_Graph Database Powered Sustainability
EY_Graph Database Powered SustainabilityEY_Graph Database Powered Sustainability
EY_Graph Database Powered Sustainability
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdf
 
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
ISDEFE - GraphSummit Madrid - ARETA: Aviation Real-Time Emissions Token Accre...
 
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafosBBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
BBVA - GraphSummit Madrid - Caso de éxito en BBVA: Optimizando con grafos
 
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
Graph Everywhere - Josep Taruella - Por qué Graph Data Science en tus modelos...
 
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4jGraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
GraphSummit Madrid - Product Vision and Roadmap - Luis Salvador Neo4j
 
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdfNeo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
Neo4j_Exploring the Impact of Graph Technology on Financial Services.pdf
 
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdfRabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
Rabobank_Exploring the Impact of Graph Technology on Financial Services.pdf
 
Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG time
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge Graphs
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
 
Neo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j Jesus Barrasa The Art of the Possible with Graph
Neo4j Jesus Barrasa The Art of the Possible with Graph
 

GraphTalk Frankfurt - Master Data Management bei der Bayerischen Versicherung

  • 1. Bay4all – über alle Touchpoints dem Kunden ein positives Service-Erlebnis vermitteln 25.6.2015 Thomas Wolf
  • 2. Den Touchpoint wählt der Kunde nach Belieben Information Vertrags- abschluss Vertrag zur Laufzeit Folgevertrag Kündigung Post Gespräch PC/Internet Call-Center
  • 3. … auch den Zeitpunkt wählt der Kunde nach Belieben … und dann bitte sofort verfügbar sein Nach der Arbeit Früh am Morgen Während die Kinder schlafen
  • 4. … deshalb sind alle Touchpoints immer aktiv
  • 5. … aber was bedeutet das für die Datenbasis? konsistent ganzheitlich aktuell keine Wartezeiten immer verfügbar
  • 7. … IST Die Bayerische wurde 1858 gegründet - Datenhistorie - Migrationshistorie mehrere unterschiedlich „alte“ Bestandssysteme - Daten sind nicht widerspruchsfrei - unterschiedlich aktuell - unterschiedliche Downzeiten
  • 9. Bestandssysteme verwenden zum Teil das VAA- Model msg.PM VAA-Model = … Verträge Sach Verträge Leben Kunden Bestandssysteme Replikation
  • 10. Einspielen der Replikationsnachrichten lesen, speichern, navigieren nodes, relations, properties Neo4J P M Transformation Basis Mapping Transaction Event Handler Label Indexer Nachricht im PM-Message Format P M PM-Message im Graphen-Format Zusammenfassung (Properties z.B. zu Vertrag) einzelne Properties kombinierte Properties Data Store Lucene Indexe exaktes Suchen, kombinierte Suche Keys, node-Adressen m Vorname m/wName node-Adresse w Auer Zöller Karl Eva 81517 58999 node-AdresseVertragsnummer 0000001 9990000 23114 44539 node-AdresseName Auer Zöller 81517 58999
  • 11. Mechanismen der Bestandsdatenreplikation … Verträge Sach Verträge Leben Kunden Bestandssysteme Gesamtbefüllung Änderungsnachrichten schwebende Änderungen
  • 12. Bestands-Services auf EINER Graphdatenbank fachliche Aufbereitung und Darstellung Erzeugen, Lesen, Ändern, Löschen
  • 13. Neo4j: nach einem Jahr in Produktion  fast komplett generische Entkopplung vom HOST  performant  professioneller Support durch Partnerschaft mit neotechnology  keine Downzeiten  eine zentrale Datenbasis für alle Kundentouchpoints 1 bis 2 Stunden für Gesamtbefüllung bei 1 Mio Verträgen max. 1 bis 2 Sekunden für Suchen  ganzheitlich, widerspruchsfrei, aktuell, immer verfügbar