Do you know more about your customer after the migration? Legacy & Data migration

Agenda

• Ways to migrate your data

• The Human Inference way

• Human Inference and Capgemini

Introducing...

Cobus

Data with a spot...

DuplicatesCapitalisation / standardization

Inconsequent

Field abuse

Wrong address

Consequences

• Declining useradoption (CRM!)– Loss of credibility in the information / in the

applicatie

• Irritatie bij klanten– Trouw, verloop, merkwaarde

• Risico problemen– Boetes, imagoschade

• Extra tijd (en geld) om data op orde te krijgen

Consequences...

• Annoyment at customers– Loyalty, churn, brandvalue

Consequences...

• Risk management– Fines, reputational damage

Consequences...

• Extra time (and money) for getting it right!

Traditional data migration

Sourcesystem

Sourcesystem

Sourcesystem

Data

-extr

act

ion

Data

-im

port

Targetsystem

WatWeetIkVanMijnKlant19 maart 2009 - Montfoort

Access, Excel, DB tools

WatWeetIkVanMijnKlant19 maart 2009 - Montfoort

Traditional data migration

Sourcesystem

Sourcesystem

Sourcesystem

Data

-extr

act

ion

Data

-im

port

Targetsystem

ETL

WatWeetIkVanMijnKlant19 maart 2009 - Montfoort

ETL...

WatWeetIkVanMijnKlant19 maart 2009 - Montfoort

ETL...

• mathematic matching/searching techniques

• vs

• smart search/matching technologies

like• Mathematical search & matching• Phonology• Morphology• Diacritic (é, Ç, ß, Ø, …)• Transliteration (non-Latin character sets ( ٻּמښھ ДЊψ…))• Etc.

Human Inference technology- Power of Knowledge -

..but with technology - you cannot interpret data -

Human Inference technologie- Power of Knowledge -

• Enhanced with ‘Knowledge-based interpretation’ – Intelligent interpretation

• Knowledge dictionaries with names and adresses• all possible meanings of various element-specific

attributes, such as abbreviations, acronyms and adjectives.

• rules for capitalization, punctuation and abbreviation are included for all elements.

• language-specific grammar rules are composed to recognize the structure of names and the context in which they appear.

• Abbreviations & Acronyms like:– Dupont & Dupont Logistique

Rue de la Gare 112Bruxelles

– Vlaamse Radio & Televisieomroep = VRT

• Context– Art Gallery Jones is not Art G. Jones

• Standardization– Beijer, Kamiel = K. Beijer = male

• Existence?– Mathijsen is correct however Matheyssen does not exist

• Transcription and Transliteration – ;Mohammad, Moehammet, Muhamet ,ڦکێگڝڗ

• Cultural aspects– The sister of Kasparov?

• Diacrits:– Güçlütürk = Goekloetoerk

Examples- Power of Knowledge -

Gebr. Dupont VervoerStationstraat 122Brussel

=

Sourcesystem

Sourcesystem

Sourcesystem

Data

-extr

act

ion

Data

-im

port

Targetsystem

Name Cleansing (HIquality Name)

Address Cleansing (HIquality Address)

Identification of duplicates

Merge Duplicates (HIquality Merge)

Enrich data (HIquality Enrich)Kn

ow

led

ge B

ase

Data migration - by Human Inference-

WatWeetIkVanMijnKlant19 maart 2009 - Montfoort

WatWeetIkVanMijnKlant19 maart 2009 - Montfoort

Clean & reliable

Sourcesystem

Sourcesystem

Sourcesystem

Data

-extr

act

ion

Data

-im

port

Targetsystem

Name Cleansing (HIquality Name)

Address Cleansing (HIquality Address)

Identification of duplicates

Merge Duplicates (HIquality Merge)

Enrich data (HIquality Enrich)

Skilled PeopleSkilled People

Data Migration MethodologyData Migration Methodology

Kn

ow

led

ge B

ase

Reference DataReference Data

Data Migration WorkbenchData Migration Workbench

On-Near-Off shore capabiltiesOn-Near-Off shore capabilties

Proven MethodologyProven Methodology

Proven Tools & AcceleratorsProven Tools & Accelerators

Secure Data CenterSecure Data Center

Human Inference & Capgemini