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Big data datacrunch


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BIG DATA : ce qu'elles sont, les enjeux, les opportunités pour le Business. Mise en bouche en perspective de DATACRUNCH

Published in: Technology, Business

Big data datacrunch

  1. 1. BIG DATAWhat ?IssuesBusiness OpportuniesHow ?
  2. 2. Definition big data consists of datasets that grow so large that they become awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing. « WIKIPEDIA »« The increasing volume and detail of information captured by enterprises,the rise of multimedia, social media, and the Internet of Things will fuelexponential growth in data for the foreseeable future ».McKinsey Global Institute,
  3. 3. Data Deluge : Evolution 2010-2015 e bas Data X 11 3, 4 milliards 4 50 000 d’abonnés pétaoctects 3G en 2015 contre 500 250 000 millions en pétaoctects s 2010 F ile Ericson ail s 30 000 X 10 M pétaoctects X61 pétaoctet (Po)= 1 000 To= 1 000 000 000 000 000 doctets International Communication Union1 zettaoctect (Zo) = 10puissance 21 octets.
  4. 4. Non Structured DataDonnées non structurées Données structurées
  5. 5. Available DATA files mail… Mobile Social Network Apps…. Comportemental DATA RFMSocio-psycho-demographic Text DATA DATA Life Instant Non structured
  6. 6. Contextual DATA
  7. 7. DATA Road Map -----> -2015---- ----------- 2013------------- 2012
  8. 8. BIG DATA : Theorical & practical Landscape Human Societi es IT system? Customers, Co nsumers ? Privacy ? Knowledges, H abilities ? Management, W ork Organisation ?
  9. 9. BIG DATA : A Thermodinamic Evolution Species (Human societies..) produce energy & modify environment (human competition, natural resources..)The Red Queen Energy Informationeffect : Run Maximization memorizationfaster to stay inplace!
  10. 10. IT ecosystemIndustries Data Created & duplicated
  11. 11. IT system, today Competitivity Réduce Cost (not Only) 4 1 EnvironmentEnvironment impact 3 adaptation 5 2 Information 6…. Memorization Resources Moore Law
  12. 12. Like that, the future is a BIG DATA CRUNCHIn a thermodynamic Schéma, BIG DATA Is Increase STORAGE + Inscrease TREATMENT + Increase DATA PRODUCTION +… Energy Dissipation critical threshold ??
  13. 13. IT System TomorrowEntropy ManagementDATA sensReduce Energie consumption
  14. 14. A BIG DATA ProcessDATA Management Multi canal (today) Cross Canal (Tomorrow) Life Instants Comportemental web mail Emission DATA … voice Capture …. Network & real Time Storage Silo traitment Predictive Actions Analysis making Reuse Contextual information PUSH
  15. 15. Consumers, customers Voice Professionnal Consumer
  16. 16. Privacy by DesignVisibility Security Transparency Prevention
  17. 17. BIG DATA = A Co-adaptativ EnvironmentE HyperstructureXT Technologic ModelINCT SpecializationIONEV U C DecentralizedO S E collectiveL E N intelligenceU R T MemeticT R EvolutivI Environment ION c
  18. 18. Data Hominem = BIG DATA KnowledgesDATA Specialists who know collect, analyzeand reuse efficiency the data in a businessway
  19. 19. Few Ways BIG DATACapture Voice = Life Instant & Comportemental DATAUnderstanding = Few to one, One to One.Interaction = ATAWAD « any time, any where, any device »
  20. 20. Industrialize singularity Several years, Customers have good technology and consumption habits since they use different Medias to behave and stay informed: internet, mobile, touch pad, interactive interface, so on. The ways of consumption could be defined as a set of situations (probably circumstances) experienced by the customers. We observe an increase of the used medias combinations during the purchase process. So it becomes very difficult to understand real customers needing in only using statistical indicators. And however it’s the goal of everyone in the company. So, how can we measure the customer experience especially to understanding their new purchases habits? Customer reality would be elusive? Our process should be as complex as their behavior? No, smarter but not especially complex. Sometimes, expanded uses methods can be a good alternative. Finally, understanding user experience within customer centricity seems the best way to industrialize singularity. ME…
  21. 21. Business in Progress Transaction space between financial and retail actors
  22. 22. BIG DATA, an opportunity for the Retail
  23. 23. Find DATA Connexity : Ex. WallMart Lab with Social Genome wihtout Social Genome
  24. 24. DATA Matching : Ex. DATALIFT R&D Project In order to see the Web of data emerge, it is necessary to provide methods and tools all along the semantic lifting process. The main objective of DATALIFT is to bootstrap semantic lifting of raw data on the Web. Interconnexion des données avec dautres jeux de données Publication sur le web de données Conversion des données en RDF en rapport avec la ou les ontologies selectionnées Sélection des ontologies pouvant décrire les données
  25. 25. BIG DATA Interaction : adiagram of Customer evolutionBring a lot of information on current changes andemerging phenomena.Communication on the efficiency andperformance will focus on the essentialsiteration.The dashboard of the future can not becompared, but it will tell us that is most importantin analysis and decision making.
  26. 26. Build a BIG DATA vision 1. Capture VoiceLife Instants 2. Understanding Comportemental DATA F O N … C T I Scoring O N Predictiv N Analysis I Expert T rules Y GRANULARITY 3. InteractionDiagram of Dashboard evolution 360° Alerts …
  27. 27. HOW ?DATACRUNCH, 13 APRIL 2012, LILLE, France RESEAU & ABLE