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