XEW Data Analysis: Competitive Intelligence System in cloud



Similar documents
XPLOR EVERYWHERE A TOOL FOR COMPETITIVE INTELLIGENCE ON THE WEB AND MOBILE

Business intelligence systems and user s parameters: an application to a documents database

How can HRM support your Business Intelligence system?

Brief description of the paper/report. Identification

Il est repris ci-dessous sans aucune complétude - quelques éléments de cet article, dont il est fait des citations (texte entre guillemets).

Odile BOIZARD EDUCATION

GUIDE OF HOW TO WRITE BIBLIOGRAPHICAL REFERENCES. 1- THE OBJECTIVE OF A BIBLIOGRAPHY.. p.2

FACULTY OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY AUTUMN 2016 BACHELOR COURSES

Vulnerability Analysis of Fire Spreading in a Building using Fuzzy Logic and its Integration in a Decision Support System

Applying the Chronographical Approach to the Modelling of Multistorey Building Projects

A Knowledge Management Framework Using Business Intelligence Solutions

Available online at Available online at Advanced in Control Engineering and Information Science

Ghizlane El Boussaidi , boul. Lévesque Est Phone : (450)

Business Intelligence System for Monitoring, Analysis and Forecasting of Socioeconomic Development of Russian Territories

CHALLENGES AND APPROACHES FOR KNOWLEDGE MANAGEMENT. Jean-Louis ERMINE CEA/UTT

TECHNOLOGY ANALYSIS FOR INTERNET OF THINGS USING BIG DATA LEARNING

Indicators' relativity & data collection dependence.

Customer Analytics. Turn Big Data into Big Value

A Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks

COURSE CODE TITLE ECTS MARKETING STRATEGIQUE I

Sri Damayanty Manullang

HGH BI Solutions. Business Intelligence & Integration. Equipping Your Organization for Effective Decision Making

IT services for analyses of various data samples

Marc R. BRADFORD Professor

Transana 2.60 Distinguishing features and functions

The Masters of Science in Information Systems & Technology

Reconstruction d un modèle géométrique à partir d un maillage 3D issu d un scanner surfacique

Toronto 26 th SAP BI. Leap Forward with SAP

COMP9321 Web Application Engineering

Big Data and Analytics: Challenges and Opportunities

Administrer les solutions Citrix XenApp et XenDesktop 7.6 CXD-203

Designing a Multi Agent System Architecture for IT Governance Platform

Course Syllabus For Operations Management. Management Information Systems

Evaluation of Business Intelligence Maturity Level in Albania Banking Systems

Smart Specialization Regional Innovation Strategy (SRI 3S) in Provence Alpes Côte d Azur

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers

Management Decision Making. Hadi Hosseini CS 330 David R. Cheriton School of Computer Science University of Waterloo July 14, 2011

Programme Course Code Language of instruction Course Contact hours ECTS MGE OIC42002F French Analyse budgétaire et tableaux de bord 24 5 MGE

Operationalise Predictive Analytics

MEng, BSc Computer Science with Artificial Intelligence

ANALYTICS STRATEGY: creating a roadmap for success

RAPPORT FINANCIER ANNUEL PORTANT SUR LES COMPTES 2014

Big Data Analytics. An Introduction. Oliver Fuchsberger University of Paderborn 2014

CUSTOMER RELATIONSHIP MANAGEMENT (CRM) CII Institute of Logistics

Millier Dickinson Blais

Visual Data Mining. Motivation. Why Visual Data Mining. Integration of visualization and data mining : Chidroop Madhavarapu CSE 591:Visual Analytics

WebFOCUS RStat. RStat. Predict the Future and Make Effective Decisions Today. WebFOCUS RStat

Introduction au BIM. ESEB Seyssinet-Pariset Economie de la construction contact@eseb.fr

A Grid Architecture for Manufacturing Database System

Integrate 'Oracle Forms', 'Oracle Reports', 'Oracle

MEng, BSc Applied Computer Science

Detailed CV Ph.D. degree, Télécom Bretagne, Brest, France. Evolutionary Computation, Combinatorial Optimization, Human-Computer Interaction

Using reporting and data mining techniques to improve knowledge of subscribers; applications to customer profiling and fraud management

Research of Smart Distribution Network Big Data Model

CompatibleOne & le SLA

Self-Service Business Intelligence

Fast and Easy Delivery of Data Mining Insights to Reporting Systems

Noel ALBERT. Assistant Professor of Marketing

INSTITUT FEMTO-ST. Webservices Platform for Tourism (WICHAI)

OPTIMIZING BUSINESS INTELLIGENCE SOLUTION FOR BANIKING IN ALBANIA

SOFTWARE DEFINED SOLUTIONS JEUDI 19 NOVEMBRE Nicolas EHRMAN Sr Presales SDS

Business Intelligence Dynamic SME. Business Intelligence

Big Data Mining Services and Knowledge Discovery Applications on Clouds

Dong-Joo Kang* Dong-Kyun Kang** Balho H. Kim***

UMR 5600 CNRS Environnement Ville Société - 18, rue Chevreul, Lyon - France (frenard@grandlyon.org)

Enterprise Resource Planning Analysis of Business Intelligence & Emergence of Mining Objects

Silvermine House Steenberg Office Park, Tokai 7945 Cape Town, South Africa Telephone:

How To Get A Computer Science Degree At Appalachian State

Outlines. Business Intelligence. What Is Business Intelligence? Data mining life cycle

Linh-Chi VO Professor

Applied Business Intelligence. Iakovos Motakis, Ph.D. Director, DW & Decision Support Systems Intrasoft SA

Technology Watch process in context: Information Systems (SI), Economic Intelligence (EI) and Knowledge Management (KM)

CONCEPTUALIZING BUSINESS INTELLIGENCE ARCHITECTURE MOHAMMAD SHARIAT, Florida A&M University ROSCOE HIGHTOWER, JR., Florida A&M University

Making confident decisions with the full spectrum of analysis capabilities

F.S. Hillier & G.T Lierberman Introduction to Operations Research McGraw-Hill, 2004

CURRICULUM VITAE. Mohamed Ali BCHIR PERSONNAL INFORMATIONS

KNOWLEDGE DISCOVERY FOR SUPPLY CHAIN MANAGEMENT SYSTEMS: A SCHEMA COMPOSITION APPROACH

BUSINESS PROCESS OPTIMIZATION. OPTIMIZATION DES PROCESSUS D ENTERPRISE Comment d aborder la qualité en améliorant le processus

JANVIER 2013 / CATALOGUE DES FORMATIONS

Business Intelligence Solutions for Gaming and Hospitality

Implementing Data Models and Reports with Microsoft SQL Server 2012 MOC 10778

Transcription:

XEW Data Analysis: Competitive Intelligence System in cloud 6th. International Conference on Information Systems & Economic Intelligence Anass El Haddadi a,b, Wahiba Bahsoun a, Bernard Dousset a a Institut de Recherche en Informatique de Toulouse, IRIT UMR 5505 Université de Toulouse, Université Paul Sabatier 118, Route de Narbonne, F-31062 Toulouse cedex 9 (France) b ENSAH, DMI, Université Med 1, Al-Hoceima, Maroc anass.elhaddadi@gmail.com, wahiba.bahsoun@irit.fr, dousset@irit.fr

Outline Introduction The analytical model of CI Information system adapted to the CI appraoch XEW the CI System in cloud Conclusion

Introduction

Introduction Competitive Intelligence System Front Office Order Entry CRM Adapter Finance SFA App Server Subsidiary Integration Broker Adapter Adapter SCM ERP Back Office CRM App Server CRM Tracking Service Adapter SCM Partner

Outline Introduction The analytical model of CI Information system adapted to the CI appraoch XEW the CI System in cloud Conclusion

The analytical model of CI Competitive Intelligence (CI) is a set of coordinated actions of research, treatment and distribution of useful information to makers, to enable the action and decision making [1, 2]. More CI is both a process and a product [3]

Outline Introduction The analytical model of CI Information system adapted to the CI appraoch XEW the CI System in cloud Conclusion

Information Systems adaptedto the CI appraoch For Patrick Romagni and Valérie Wild, the definition of an information system adapted to the CI approach is as follows: organized set of procedures, at any time, to give decision-maker a representation of the company in its environment and its market. It produces information to assist in executive functions, management and decision-making. Facilitate decisions, to automate a number of actions or by providing to decision makers the necessary information for decision-making, Coordinate the processing of information, Store sustainably information, Improve data processing: the creation of information directly usable by decision makers.

Information Systems adaptedto the CI appraoch Reduce the number of vertical coordination by reducing managements layers, Improved environmental monitoring, An opening-up by a crosscommunication, Relationships based on complementarities business, A better adaptation to market dynamics.

Information Systems adaptedto the CI appraoch The advantage of this type of information system : Project management monitoring, Information sharing, Custom interface Collecting more accurate and targeted, Processing, analysis, storage Dissemination

Information Systemsadaptedto the CI appraoch 1. Develop 2. Choose 3. Identify & Prioritize 4. Identify & select 5. Collect & Evaluate 6. Organize & Remember 7. Validate & Stream 8. Analyze & Interpret 9. Validate & Spread

Information Systemsadaptedto the CI appraoch The model described is based on two main models: A multidimensional representation of documents: which can transfer qualitative data into quantitative data. The objective of this model is to get at the end, a unifying view of the documents collected. A function model,which aims to provide a set of generic and combinatory functions to build different kind of indicator as needed for analysis.

Outline Introduction The analytical model of CI Information system adapted to the CI appraoch XEW the CI System in cloud Conclusion

History 1983 3D Visualization of PCA (Master) 1985-87 3D parametric space : T. Benjamaà (Thesis) 1987 Trilogy 3D (PCA, FA, HC, Partitioning) 1989-93 Text mining, evolution : T. Dkaki (Thesis) 1993 1 Tetralogy Platform (4D) 1998 Interactiv Visualization of HC (Master), emmergence (Master) 1999 Design of CI system : M. Salle (Thesis & Medesiie project) 2002 Engineering of the need : T. Zid (Thesis et Medesiie project) 2003 Large graphs, geostrategy: S. Karouach (Thesis) 2004 Adequacy with the companies profiles : S. Hussein (Thesis) 2005 Morphing of evolutionary graphs: S. Karouach (post doc) 2009 VisuaGraph: E. Loubier (Thesis) 2009 Xplor V1: I Ghalamalah (Thesis) 2011 Xplor V1.1 & XEW: A. El Haddadi (Thesis)

Tetralogy Platform - TM Dictionary+ or - Extraction of the dictionaries Load diagram Synonyms

Tetralogy Platform - TM Dictionary of multi-terms

Tetralogy Platform - TM 2D Crossings Square matrix Asymmetrical matrix

Tetralogy Platform - TM 3D Crossings Third variable Filter

Tetralogy Platform - DM for the matrix treatment proposal of several algorithms of sorting supervised generation of crossing matrix 3D spreadsheet adapted to big size matrix (2 and 3 D zooms) for multidimensionnal analysis 3D and 4D interactive visualizations synchronization of local or distant charts visualization of trajectories and procrustean rotations (MFA) for classifications interactive hierarchical trees with class export partitioning of graphs, graphs of classes segmentation for the geographical maps

Tetralogy Platform - DM Sorting algorithms of matrix Connexity zoom diagonal blocks zoom

Tetralogy Platform DM (PCA) 4D map of co-ordinates Synchronisation Correlation ring

Tetralogy Platform DM (FCA)

Tetralogy Platform DM (MFCA)

TetralogyPlatform DM(AHC) de( A, B) = de( g, h) = ( g i hi)² dm( A, B) { de( xk, yl )} i= 1, n Min = dm( A, B) = { de( xk, yl )} k, l Max k, l e d ( xk, yl k l dµ( A, B) = A B ) Niveau de coupure à 8 classes Niveau de coupure à 4 classes

Tetralogy Platform - DM Supervised method K initial classes 4 classes 6 classes

Tetralogy Platform Data Visualization faibles. Linear distribution Evolution of coloration Data selection Choice of nonlinear scale weak signals detection

Tetralogy Platform Data Visualization Absent coutry. Country on the decline Country in emergence Mapin relative mode : trend study Classification exportation Country class size Levelof cut

Tetralogy Platform Data Visualization

Tetralogy Platform Data Visualization

Tetralogy Platform Tetralogy platform caracteristics it is a coherent whole of inter-operative prototypes, use a single standard for the format of the data, its graphic interface is homogeneous, resources and methods are shared via the network. Research use evaluation support of methods, tools and BI products, many examples, on the scale, already analyzed. Application domain : strategic watch Scientific watch (scientometry, indicators, evaluation) Technologic watch (patent rights, products, proceeded) Business watch (markets, competitors, substitutes)

Tetralogy to XEW Advantage Processing speed (ram, hash coding) Disadvantage Limited size (<5000*5000/2D, < 25000*250*4/3D) The result is that more and more space is lost! (sparse matrix) Loading time Managing domain names 2 or 3 variables

Tetralogy to XEW

Life Cycle of XEW model Validation and dissemination Planification Indicators for analysis Information Retrieval Multidimentional representation of documents Homogenization and structuring documents

Sourcing Web Service Website Internet Invisible Web Newsgroups Mailing-lists Newsletters 5000 Professional DB Patents Papers, thesis, Economic data Network and contact Experts Organism

Sourcing Web Service

Sourcing Web Service in cloud

Sourcing Web Service in cloud Crawling and Scraping WS Front Office Order Entry CRM Adapter Finance SFA App Server Subsidiary Integration Broker Adapter Adapter SCM ERP Back Office CRM App Server CRM Tracking Service Adapter SCM Partner

Open Source NoSQL Databases

Data Analysis WS

Data Analysis WS

XEW the CIS Data Analysis WS Virtualization App App App App App App OS OS OS Operating System Hypervisor Hardware Hardware

Data Analysis WS Storage virtualization Application virtualization

Data Analysis WS Storage virtualization uses virtualization to enable better functionality and more features in computer data storage systems.

Data Analysis WS Application virtualization is software technology that encapsulates application software from the underlying operating system on which it is executed. A fully virtualized application is not installed in the traditional sense, although it is still executed as if it were. The application behaves at runtime like it is directly interfacing with the original operating system and all the resources managed by it, but can be isolated or sandboxed to varying degrees.

Open Source Cloud Computing Open Source Hypervisors

Open Source Cloud Computing Open Source Compute Clouds(IaaS)

Open Source Cloud Computing Open Source Cloud Storage Software

Data Analysis WS

Data Analysis WS

ixew: iphone Xplor EveryWhere

Data Analysis WS

Outline Introduction The analytical model of CI Information system adapted to the CI appraoch XEW the CI System in cloud Conclusion

Conclusion KM of Tetralogy and XEW 1.0 Data Stream Mining WS of crawling and scraping: USPTO, IEEE

Conclusion Governance in cloud

Conclusion

References M. Salles, "Projet MEDESIIE : Méthode MEDESIIE de définition du besoin en intelligence économique des PME", Université Toulouse I, 2002. HAAG S., "Management Information Systems for the Information Age, Third Edition.". Third Edition. McGraw-Hill Ryerson, 2006. GILAD B., "The Futur of Competitive Intelligence, Contest for the Profession s Soul", Competitive Intelligence Magazine, 11(5), 22, 2008. R. G. Vedder, M. T. Vanecek, C. S. Guynes, and J. J. Cappel, "CEO and CIO Perspectives on Competitive Intelligence", Communications of the ACM, Vol. 42, N 8, 1999. P.S. Seligman, G.M. Wijers, H.G. Sol, Analyzing the structure of I.S. methodologies, an alternative approach, In proceedings of the Conference in information systems, The Ntherlands, 1989. M. Salles, Modélisation des situations de décision dans une méthode d'ingénierie du besoin en I.E, Conférence IERA, Intelligence Economique : Recherches et Applications, Nancy, France, 2003. M. Salles, De l'analyse du besoin des PME en IE à l'intelligence Territoriale. Colloque Européen d'intelligence Economique, Poitiers Futuroscope, ESCEM Poitiers, p. 414-427, Poitiers, France, 2005. A. David, O. Thiery, Application of EQuA2te Architecture. Economic Intelligence, 2002. N. Bouaka, «Développement d un modèle pour l explication d un problème décisionnel : un outil d aide à la décision dans un contexte d Intelligence Economique. Thèse de doctorat de l université Nancy 2, 2004. PH. Kislin, Modélisation du problème informationnel du veilleur dans la démarche d intelligence économique. Thèse de doctorat de l université Nancy 2, France, 2007. P. Romagni, Wild V., L'Intelligence économique au service de l'entreprise, ou l'information comme outil de gestion. Les Presses du Management, 1998 Club Informatique des Grandes Entreprises Françaises, «Intelligence économique et stratégique». Rapport Cigref, 2004. Ghalamallah, Proposition d un modèle d analyse exploratoire multidimensionnelle dans un contexte d intelligence economique, doctorat de l université de toulouse, 18 décembre (2009). F. Jakobiak, L'intelligence économique : la comprendre, l'implanter, l'utiliser. Les éditions d organisation, 2006. A. El haddadi, B. Dousset, I. Berrada and I. Loubier, Les multi-sources dans un contexte d Intelligence Economique, EGC 2010, P A1-125 A1-136, 2010. El haddadi, B. Dousset. and I. Berrada., Xplor everywhere a tool for competitive intelligence on the web and mobile, VSST 2010, 25-29 Octobre, Toulouse France, 2010. H. Hatim, A. El haddadi, H. El bakkali, B. Dousset, and I. Berrada, Approche générique de contrôle d accés aux donénes et aux traitements dans une plate-forme d intelligence économique, colloque Veille Stratégique et technologique, 2010.

Thankyou!!! SIIE -February 12, 13 and 14th., 2015 at Hammamet, Tunisia - Anass EL HADDADI - anass.elhaddadi@gmail.com