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TOOLS FOR DATA GOVERNANCE. PASSIONATE BY DATA AND THE ACCURACY OF THE RESULTS. Data are at the heart of the I.S. and are the elements allowing BUSINESS CONTINUITY. DOMAIN. APPLICATIONS. Data. APPLICATIONS. DBMS. REVER. Data Access. Data Access. PROGRAMS. DBMS. PROGRAMS. Data. - PowerPoint PPT Presentation
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TOOLS FOR DATA GOVERNANCE
PASSIONATE BY DATA AND
THE ACCURACY OF THE RESULTS
DOMAIN
APPLICATIONS
REVER
PROGRAMS
DBMSData Access
Processings
Presentation
Programs management(web server, transactional, jcl, …)
Data
Data
DBMSData Access
ProcessingsPresentation
Programs management
REVER
APPLICATIONS
PROGRAMS
Data are at the heart of the I.S.
and are the elements allowing BUSINESS
CONTINUITY
SOLUTIONS
EVOLVE-EASY
DEV-EASY
DATA QUALITY
S.E.A.L.
DOC-EASY
SHARED MASTERY
ÉVOLUTIONS WITHOUT RISK
MEASURES CORRECTIONS
DB-MAINKNOWLEDGE MODELLING
EXTRACTIONS ANONYMIZATIO
NS
ACCESS LAYER DEVELOPMENT ACCELERATOR
ARCHITECTURE
CHARACTERISTICS
INDUSTRIAL AUTOMATED CONTROLS
Integrated in the proccesses Applications independant
REVERSOLUTION
S ADAPTABLE
GÉNÉRIC Methods Tools
FLEXIBLE PROGRAMMABLE
SERVICES
SUBCONTRACTING SIDE BY SIDE
Training Support Follow-up
SOLUTIONS
EVOLVE-EASY
DEV-EASY
D.I.S.Q.
S.E.A.L.
DOC-EASY
DB-MAIN
1 OUT OF 2 COMPANY declares
1 OUT OF 4 COMPANY déclares
« WE DO NOT KNOW WHICH ARE THE REAL USES OF OUR
DATA »
« THE DATA AT THE DISPOSAL OF DEVELOPERS
WERE USED FOR OTHER PURPOSES »
WHAT STUDIES TELL US**Ponemon Institute
THE MANAGEMENT OF THE DATA USES 60 % OF THE TESTING TIME
THE DATA RELATED TO A CONCEPT (customers, suppliers, products)
ARE SPREAD IN VARIOUS TECHNICAL DATABASES
STUDIES (follow)
nameSMITH
….
tittleMISTERMADAM
???
sexMAN
WOMENUNKNOW
N
CLIENTS
name address Client Nbr
SMITH NY CLI 001
DEFINITIONS
DATAGeneric name covering the notions of: « category» (name) designed by
« column » « value» (Smith) designed by
« content »
TABLECollection of grouped columns
to represent a concept
LINKAll type of relations between columns
There are numerous "types of link: dependency, referential, redundancy,
…
REFERENTIAL LINKThe column establishing a link between the content of 2 tables
REDONDANCY LINKThe column which takes the content of another column at time T
ORDERS réf. Cli. NbrOrder Nbr Amount Delivery
ad
ORD 001 50 € PHOENIX
CLI 001
ORD 002 100 € NY CLI 001
DEFINITIONS
CLIENTS
Name Address Client Nbr
SMITH NY CLI 001
CLIENTS
Name Address Client Nbr
SMITH NY CLI 001
ORDERS réf. Cli. NbrOrder Nbr Amount Delivery
ad
ORD 001 50 € PHOENIX
CLI 001
ORD 002 100 € NY CLI 001
DATABASETechnical « container » grouping a collection of tables
COPYReproduction of an "original" content for processing
purposes
PROCESSTerm which denotes either manual processes, or automated
processes, or any combination of manual and automated processes
DEFINITIONS
« clients »« payments»
DOSSIER: tables collection linked directly or indirectly with a main table
DEFINITIONS
CLIENTS BASE ORDERS BASE PAYMENTS BASE
The notion of dossier is independent from the "technical" implementation and is mostly "transverse"
in databases
DEFINITIONS
S.E.A.L. : Select, Extract, Anonymize & Load
THE NEEDS
S.E.A.L
S.E.A.L
PRODUCTION DATABASES
S.E.A.L. DATABASE .
PRODUCTSORDERS PAYMENTSCLIENTS
« TECHNICAL »DESCRIPTION OF THE TABLES AND
COLUMNS
Project manager
DATABASESSELECTION
ADDITION REFERENTIAL LINKS REDONDANCY LINKS
« FUNCTIONAL »DESCRIPTION
THE DATA YOU HAVE
REDONDANCY LINKS
REFERAL LINKS
PRODUCTSORDERS PAYMENTSCLIENTS
THE DATA YOU HAVE
SELECT THE « NECESSARY AND SUFFICIENT » DATA
FOR THE FORECASTED PROCESSINGS
DEFINE THE DOSSIERS
SELECT THE CONTENTS
S.E.A.L. database
« FUNCTIONAL »DESCRIPTION
TABLES LIST Ordered in
THE ORDER OF THE PROCESSINGS
COMBINATION OF THE SELECTION
CRITERIA
THE DATA « YOU WANT »
PROJECT M
CAMPAIGN i CAMPAIGN j
THE DATA « YOU WANT »
CAMPAIGN jSELECT the CONTENTS
« Name clients = SMITH »
THE DATA THAT « YOU WANT »
COPIES CONTROLS
COLUMN NOT TO BE USED FOR SELECTING CONTENTS
COLUMN YOU MAY NOT COPY
LIMIT TO THE NUMBER OF DOSIERS TO BE COPIED
e,g, minimum 100 dossiers
THE PROTECTIONS
RULES
MASKING
LIST
CALCULATION
Specific functions
ANONYMIZATION
COLUMNS RÉGLESPROJECTS/CAMPAIGN
S Clientname
Rule A(maskin
g)
PROJ M/
CAMP i
PROJ M/
CAMP j
Client name
Rule B(list)
Birth date
Rule C(calculated)
PROJ M/CAMP i
PROJ M/
CAMP j
Birth date
Rule D(calculated)
ANONYMIZATION
EXTRACTION ENGINE
ALLOWS THE EXTRACTION OF THE DOSSIERS
GENERATION ENGINE
ADD LINES AND 3POPULATE 3THE COLUMNS
ANONYMIZATION ENGINE
ANONYMIZE THE CONTENTS
STORAGE ENGINE
GIVES THE RESULTING DOSSIERS
REPORT ENGINE
PRODUCES THE REPORTS AND STATISTICS
THE ENGINES
THE ANONYMIZATION ENGINE
DATABASE FROM THE SOFTWARE PACKAGE (ERP,CRM,….)
DATA TO BE PROCESSED
ANONYMIZED DATA TO
BE PROCESSED
REAL CONTENTS FICTIVE
CONTENTSCORRESPONDENC
E
ANONYMIZATIONS
EXPORT
PROCESSED DATA
PROCESSED ANONYMIZE
D DATA
RE-IDENTIFICATIO
N
PROCESSING
IMPORT
PROCESSING
EXAMPLE: SOFTWARE PACKAGES
YOU WANT TO
COPY INTEGRATE
ONE DOSSIER
SEVERALDOSSIERS
ALL THE CONTENTS from
one or more databases
S.E.A.L. FUNCTIONS
In your applications or packages
THE S.E.A.L. PRODUCTS
COPY PART OF THE DATA
COPY A COMPLETE DATABASE
AN INDIVIDUAL DOSSIER SEVERAL DOSSIERS
ONLY THE TABLES NEEDED FOR PROCESING
BAN TO COPY CERTAIN COLUMNS
OBLIGATION TO COPY A MINIMUM Nbr OF
DOSSIERS
CONTENTS ANONYMIZATION
S.E.A.L. The products PROTECTING all COPIES of your DATA
PROTECTIONS SUMMARY
FUNCTIONAL APPROACH
INTUITIVE AND FRIENDLY
INTERFACE
RULES AND ANONYMIZATION DESCRIPTIONS
RE-USE
PARTIAL COPIES
DÉFINITIONS AND
OPERATIONS STORED IN A SPECIALIZED
DATABASE
QUICK INSTALLATION
AND CONFIGURATION
MONO DATABASEMULTI
DATABASES
RÉDUCTION OF THE TECHNICAL
RESSOURCES
MAINTAIN COHERENCE
SIMPLE
INCREASE OF PRODUCTIVITY
COSTS DECREASE
FUNCTIONALITIES TECHNICAL ADDED VALUE
S.E.A.L. MAIN ADVANTAGES
THE MECHANISMS USED IN S.E.A.L. ARE INDEPENDENT FROM THE DATA "SEMANTICS"
S.E.A.L. IS DIRECTLY USABLE BY EVERY TYPES OF"BUSINESSES"
« AFFORDABLE »PRICING
S.E.AL. ADVANTAGES (more)
THANK YOU FOR YOUR TIME
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