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TOOLS FOR DATA GOVERNANCE

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.

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TOOLS FOR DATA GOVERNANCE

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  1. TOOLS FOR DATA GOVERNANCE PASSIONATE BY DATA AND THE ACCURACY OF THE RESULTS

  2. 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 REVER Processings Presentation Processings Presentation Programs management (web server, transactional, jcl, …) Programs management

  3. SOLUTIONS SHARED MASTERY ÉVOLUTIONS WITHOUT RISK • DOC-EASY • EVOLVE-EASY • DB-MAIN KNOWLEDGE MODELLING • S.E.A.L. • DEV-EASY EXTRACTIONS ANONYMIZATIONS ACCESS LAYER DEVELOPMENT ACCELERATOR • DATA QUALITY MEASURESCORRECTIONS

  4. ARCHITECTURE

  5. CHARACTERISTICS • AUTOMATED • CONTROLS • Integrated in the proccesses • Applications independant • INDUSTRIAL • REVER • SOLUTIONS • GÉNÉRIC • Methods • Tools • FLEXIBLE • PROGRAMMABLE • ADAPTABLE • SUBCONTRACTING • SIDE BY SIDE • Training • Support • Follow-up • SERVICES

  6. SOLUTIONS • DOC-EASY • EVOLVE-EASY • DB-MAIN • S.E.A.L. • DEV-EASY • D.I.S.Q.

  7. WHAT STUDIES TELL US**Ponemon Institute 1 OUT OF 2 COMPANY declares « WE DO NOT KNOW WHICH ARE THE REAL USES OF OUR DATA » 1 OUT OF 4 COMPANY déclares « THE DATA AT THE DISPOSAL OF DEVELOPERS WERE USED FOR OTHER PURPOSES »

  8. STUDIES (follow) THE DATA RELATED TO A CONCEPT (customers, suppliers, products) ARE SPREAD IN VARIOUS TECHNICAL DATABASES THE MANAGEMENT OF THE DATA USES 60 % OF THE TESTING TIME

  9. DEFINITIONS • DATA • Generic name covering the notions of: • « category» (name) designed by « column » • « value» (Smith) designed by « content » TABLE Collection of grouped columns to represent a concept LINK All type of relations between columns There are numerous "types of link: dependency, referential, redundancy, …

  10. DEFINITIONS REFERENTIAL LINK The column establishing a link between the content of 2 tables REDONDANCY LINK The column which takes the content of another column at time T

  11. DEFINITIONS DATABASE Technical « container » grouping a collection of tables PROCESS Term which denotes either manual processes, or automated processes, or any combination of manual and automated processes COPY Reproduction of an "original" content for processing purposes

  12. DEFINITIONS DOSSIER: tables collection linked directly or indirectly with a main table « clients » « payments»

  13. DEFINITIONS The notion of dossier is independent from the "technical" implementation and is mostly "transverse" in databases CLIENTS BASE ORDERS BASE PAYMENTS BASE

  14. S.E.A.L. : Select, Extract, Anonymize & Load

  15. THE NEEDS

  16. S.E.A.L

  17. S.E.A.L

  18. THE DATA YOU HAVE PRODUCTION DATABASES CLIENTS ORDERS PAYMENTS PRODUCTS S.E.A.L. DATABASE . DATABASES SELECTION « TECHNICAL » DESCRIPTION OF THE TABLES AND COLUMNS • ADDITION • REFERENTIAL LINKS • REDONDANCY LINKS «FUNCTIONAL » DESCRIPTION Project manager

  19. THE DATA YOU HAVE CLIENTS ORDERS PAYMENTS PRODUCTS REFERAL LINKS REDONDANCY LINKS

  20. THE DATA « YOU WANT » S.E.A.L. database SELECT THE «  NECESSARY AND SUFFICIENT » DATA FOR THE FORECASTED PROCESSINGS « FUNCTIONAL » DESCRIPTION DEFINE THE DOSSIERS TABLES LIST Ordered in THE ORDER OF THE PROCESSINGS SELECT THE CONTENTS COMBINATION OF THE SELECTION CRITERIA

  21. THE DATA « YOU WANT » PROJECT M CAMPAIGN j CAMPAIGN i

  22. THE DATA THAT « YOU WANT » SELECT the CONTENTS «  Name clients = SMITH » CAMPAIGN j

  23. THE PROTECTIONS COLUMN NOT TO BE USED FOR SELECTING CONTENTS COPIES CONTROLS COLUMN YOU MAY NOT COPY LIMIT TO THE NUMBER OF DOSIERS TO BE COPIED e,g, minimum 100 dossiers

  24. ANONYMIZATION RULES MASKING LIST CALCULATION Specificfunctions

  25. ANONYMIZATION PROJECTS/ CAMPAIGNS COLUMNS RÉGLES PROJ M/ CAMP i Client name Rule A (masking) PROJ M/ CAMP j Client name Rule B (list) PROJ M/ CAMP i Birth date Rule C (calculated) PROJ M/ CAMP j Birth date Rule D (calculated)

  26. THE ENGINES 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

  27. THE ANONYMIZATION ENGINE

  28. EXAMPLE: SOFTWARE PACKAGES DATABASE FROM THE SOFTWARE PACKAGE (ERP,CRM,….) EXPORT IMPORT DATA TO BE PROCESSED PROCESSED DATA PROCESSING REAL CONTENTS FICTIVE CONTENTS CORRESPONDENCE ANONYMIZATIONS RE-IDENTIFICATION ANONYMIZED DATA TO BE PROCESSED PROCESSED ANONYMIZED DATA PROCESSING

  29. THE S.E.A.L. PRODUCTS YOU WANT TO COPY INTEGRATE ALL THE CONTENTS from one or more databases ONE DOSSIER SEVERAL DOSSIERS S.E.A.L. FUNCTIONS In your applications or packages

  30. PROTECTIONS SUMMARY S.E.A.L. The products PROTECTING all COPIES of your DATA 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

  31. S.E.A.L. MAIN ADVANTAGES ADDED VALUE FUNCTIONALITIES TECHNICAL FUNCTIONAL APPROACH MONO DATABASE MULTI DATABASES MAINTAIN COHERENCE INTUITIVE AND FRIENDLY INTERFACE QUICK INSTALLATION AND CONFIGURATION SIMPLE RULES AND ANONYMIZATION DESCRIPTIONS RE-USE DÉFINITIONS AND OPERATIONS STORED IN A SPECIALIZED DATABASE INCREASE OF PRODUCTIVITY PARTIAL COPIES RÉDUCTION OF THE TECHNICAL RESSOURCES COSTS DECREASE

  32. S.E.AL. ADVANTAGES (more) 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

  33. THANK YOU FOR YOUR TIME

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