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Le big data à l'épreuve des projets d'entreprise
Le document traite des défis et des solutions liés à l'utilisation des technologies Big Data dans les projets d'entreprise, en mettant l'accent sur des outils comme MongoDB et Elasticsearch. Il aborde des concepts clés tels que la gestion des données en temps réel, la scalabilité et l'importance des métadonnées pour la transformation des données en informations exploitables. En outre, il présente des exemples d'application de ces technologies dans divers cas d'utilisation, soulignant leur rôle dans l'amélioration des décisions commerciales et de l'expérience client.
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Le big data à l'épreuve des projets d'entreprise
- 1. LOGO du client BigData à l’épreuve des projets d’entreprise #2013
- 2.
- 3. Pas tout àfait….
- 7. Et des camionsil y en a ….
- 8. Et des camionsil y en a ….
- 9. Ecotaxe § Flux entrant24/7 • 2 000 points par seconde • 200 paquets par seconde § Flux sortant 24/7 • 3* 200 paquets par seconde § Conservation 3 mois • 1, 5 Milliard de paquets • 7 téraoctets
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- 11. Big Data Règle des3V Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. gartner.com
- 12. Big Data Règle des3V Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. gartner.com Variety Volume Velocity
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- 14.
- 15. Toujours plus, etplus encore… Quantité de données Temps
- 16. The Inverted U Qualitéde décision Peter Morville Sous information Sur information Quantité d’informations U U/
- 17.
- 18. Data è Information Pourcréer du sens il faut transformer la donnée en information
- 19. métadonnées Donnée propriétés Exemple : individu,événement, équipement
- 20. métadonnées Exemple : tags,chronologie, géolocalisation, relations, notes, commentaires…. Métadonnées Donnée propriétés
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- 22. Cycle de création Information Data……………………………………………....... Méta - Information Création Enrichissement timeline
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- 29. Ecotaxe § Flux entrant24/7 • 2 000 points par seconde • 200 paquets par seconde § Flux sortant 24/7 • 3* 200 paquets par seconde § Conservation 3 mois • 1, 5 Milliard de paquets • 7 téraoctets #Volume #Velocity
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- 31. RETEX MongoDB Changement deparadigme § En phase amont Lutter contre la peur des décideurs / la résistance des équipes § En phase de spécifications /réalisation Intégrer l’approche documentaire vs approche relationnelle Former les équipes de développement Exemple : logique transactionnelle § En phase de production Lutter contre l’hébergement traditionnel / san Favoriser l’approche horizontale vs verticale
- 32. Vertical / Horizontal «Scalabilité » Verticale Si besoin de plus de puissance • on ajoute de la mémoire …. • puis on remplace par un serveur de gamme plus puissante Corollaire : les machines sont surdimensionnées pour absorber une augmentation potentielle de charge
- 33. Vertical / Horizontal «Scalabilité » Verticale Si besoin de plus de puissance • on ajoute de la mémoire …. • puis on remplace par un serveur de gamme plus puissante Corollaire : les machines sont surdimensionnées pour absorber une augmentation potentielle de charge
- 34. Vertical / Horizontal «Scalabilité» Horizontale Si besoin de plus de puissance • on ajoute des serveurs Corollaire : linéarisation du coût / usage
- 35. Vertical / Horizontal «Scalabilité» Horizontale Si besoin de plus de puissance • on ajoute des serveurs Corollaire : linéarisation du coût / usage
- 36. MongoDB Ne pas utilisezMongoDB si votre système est transactionnel, pour le reste … § Avantages • Qualité de la documentation • Mise en œuvre rapide • Versatilité § Inconvénient • Sharding pas si simple ! § Bénéfices • Agilité fonctionnelle • Evolution du modèle aisée / versionnement natif • Agilité technique • Alignement matériel par rapports aux usages
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- 41. RETEX Elasticsearch CQRS Command QueryResponsibility Segregation Command Query Store Index EventBus
- 42.
- 43. RETEX Rubedo Premier CMSopen-source basé sur un socle NoSQL + Dans un monde où LAMP est LA Norme NoSQL, mais pour quoi faire ?
- 44. NoSQL et Gestionde contenus § Les CMS gèrent des Contenus … … structurés et classés
- 45. Rubedo : comparaisondes approches Approche relationnelle type MySQL Pour un type de contenu : 6 tables Pour 10 types de contenus : 29 tables 1 requête unitaire = 6 tables et 2 jointures Approche NoSQL documentaire type MongoDB Pour un type de contenu : 1 collection Pour 10 types de contenus : 1 collection 1 requête unitaire : 1 collection
- 46. Rubedo : lesatouts du NoSQL § Atouts Fonctionnels § Limites & précautions • Souplesse de modélisation • Evolutivité dans le temps • Fonctionnalités de Recherche • • Pas de transactions Déport des règles métiers dans la couche applicative § Atouts Techniques • • • • • Performances en lecture/écriture Stockage de grands volumes Montée en charge linéaire Gestion des fichiers intégrée (MongoDB) • Sécurité centralisée • Framework de développement indispensable ! Certaines typologies de projets peuvent nécessiter une architecture hybride (site de ecommerce complexe par exemple)
- 47. Rubedo : lescas d’usage Performances & Volumétrie Mobilité Ergonomie Souplesse Use cases Recherche & Géolocalisation Ouverture & Extensibilité § Portails à fort trafic ou volumétrie § Contenus géo-localisés & cartographie § Moteurs de recherche verticaux § Plateformes multi-sites § Plateformes de contribution décentralisées § Sites mobiles
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- 50. LOGO du client Mercide votre attention
- 51. Elasticsearch Revolutionizing Data Search andAnalytics Richard Maurer– SEMEA Territory Manager
- 52. Agenda • Purpose ofElasticsearch • Features of Product • Customer Examples • Company Overview • Commercial Offerings • Resources
- 53. Purpose of Elasticsearch • Organize data and make it easily accessible – Through powerful search and analytics – Easily consumable (even for non-data scientists) – Elegantly handles extremely large data volumes – Delivers results in real time • Technology stack agnostic • Used across all market verticals
- 54. Features of Elasticsearch • Structured & unstructured search • Advanced analytics capabilities • Unmatched performance • Real-time results • Highly scalable • User friendly installation and maintenance
- 55. User: GitHub Searches 20TBof data, 1.3 billion files and 130 lines of code using Elasticsearch
- 56. User: Foursquare Searches 50,000,000venues every day using Elasticsearch
- 57. User: Fog CreekSoftware Searches 40,000,000,000 (40 billion) lines of code in real-time using Elasticsearch
- 58. User: StumbleUpon Delivers millionsof recommendations every day using Elasticsearch
- 59. Example: Email Archiving EmailArchiving of 2 Petabytes of data across 100’s of servers Big data, structured and unstructured
- 60. Example: Support Agents CustomSupport – Search, Facets, and Reports Real time metrics
- 61. Unprecedented Uptake Elasticsearch hasmore than 5 Million downloads … and 400,000 more each month Cumulative Cumulative m
- 62. Company Overview More than5 million downloads 400,000 New Downloads per Month 1000s of Mission Critical Implementations Top Investors: Benchmark Capital, Index Ventures • Seasoned Executive Team • • • • – Founded by Creator of Elasticsearch – Seasoned Executives from SpringSource
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- 64. User Raves Chris Cowan@uhduh I’m in love with @elasticsearch! I want to use it for everything right now! Alain Richardt @alaincxs Moving ffrom #solr to # Elasticsearch is like upgrading from a Reliant Robin to a McLaren F1 Pete Connolly @peteconnolly Two really useful and productive days of training from @kimchy and @uboness all about #elasticsearch. Best training course in years Cyril Lacôte @clacote #ElasticSearch is the s*&t. Amazingly simple and powerful. Open source is awesome. That's made my day. Logan Lowell @fractaloop Tweaking @elasticsearch for huge indexes can be fun. I'm very glad the IRC channel is so helpful too.
- 65. Product Offerings: Support ThroughoutYour Project 1. Core Elasticsearch Training 2. Development and Production Support 3. Technical Account Manager
- 66. 1: Training Core ElasticsearchTraining • Two day classroom training • Delivered by Elasticsearch developers 1. Worldwide Public Courses 2. Onsite Training Course
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- 68. 3: Technical AccountManager • • • • • Named technical resource Single point of contact into Elasticsearch Onboarding call to assess your goals Four health checks per year Go-to expert to drive success with your Elasticsearch deployment
- 69. Resources • www.elasticsearch.com • www.elasticsearch.org • User Groups: http://www.elasticsearch.org/community/forum/ • Contact: Richard Maurer Territory Manager [email protected]
- 70. Le Big Dataà l'épreuve des projets d'entreprise Yann Aubry Regional Director
- 71. The Big DataUnknown
- 72. Top Big DataChallenges? Translation? Most struggle to know what Big Data is, how to manage it and who can manage it 3 Source: Gartner
- 73. Understanding Big Data– It’s Not Very “Big” 64% - Ingest diverse, new data in real-time 15% - More than 100TB of data 20% - Less than 100TB (average of all? <20TB) from Big Data Executive Summary – 50+ top executives from Government and F500 firms 4
- 74. When To UseHadoop, NoSQL
- 75. 6 Applications CRM, ERP, Collaboration,Mobile, BI Data Management Online Data RDBMS RDBMS Offline Data Hadoop Infrastructure OS & Virtualization, Compute, Storage, Network EDW Security & Auditing Management & Monitoring Enterprise Big Data Stack
- 76. Consideration – Onlinevs. Offline Online • Real-time • Low-latency • High availability 7 vs. Offline • Long-running • High-Latency • Availability is lower priority
- 77. Consideration – Onlinevs. Offline Online 8 vs. Offline
- 78. MongoDB/NoSQL Is Goodfor! 360° View of the Customer Fraud Detection User Data Management Content Management & Delivery Reference Data Product Catalogs 9 Mobile & Social Apps Machine to Machine Apps Data Hub
- 79. Hadoop Is Goodfor! Risk Modeling Recommendation Engine Ad Targeting Transaction Analysis Trade Surveillance Network Failure Prediction 10 Churn Analysis Search Quality Data Lake
- 80. How To UseThe Two Together?
- 81. Case Study Insurance leadergenerates coveted 360-degree view of customers in 90 days – “The Wall” Problem • No single view of customer • 145 yrs of policy data, 70+ systems, 15+ apps • 2 years, $25M trying to aggregate in RDBMS – failed Why MongoDB • Agility – prototype in 5 days; production in 90 days • Dynamic schema & rich querying – combine disparate data into one data store • Hot tech to attract top talent 12 Results • Increased call center productivity • Better customer experience, reduced churn, more upsell opps • Dozens more projects in the works to leverage this data platform
- 82. Machine Learning Ad-Serving Algorithms MongoDB Connector for Hadoop • • • • • 13 Catalogsand products User profiles Clicks Views Transactions • User segmentation • Recommendation engine • Prediction engine
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- 84. MongoDB The leading NoSQLdatabase General Purpose 15 Document Database OpenSource
- 85. MongoDB Vision To providethe best database for how we build and run apps today Build – New and complex data – Flexible – New languages – Faster development 16 Run – Big Data scalability – Real-time – Commodity hardware – Cloud
- 86. Fortune 500 &Global 500 • 10 of the Top Financial Services Institutions • 10 of the Top Electronics Companies • 10 of the Top Media and Entertainment Companies • 8 of the Top Retailers • 6 of the Top Telcos • 5 of the Top Technology Companies • 4 of the Top Healthcare Companies 17
- 87. Global Community 5,000,000+ MongoDB Downloads 100,000+ OnlineEducation Registrants 20,000+ MongoDB User Group Members 20,000+ MongoDB Days Attendees 20,000+ MongoDB Management Service (MMS) Users 18
- 88. MongoDB Features • JSONDocument Model with Dynamic Schemas • Full, Flexible Index Support and Rich Queries • Auto-Sharding for Horizontal Scalability • Built-In Replication for High Availability • Text Search • Advanced Security • Aggregation Framework and MapReduce • Large Media Storage with GridFS 19
- 89. MongoDB Business Value EnablingNew Apps Faster Time to Market 20 Better Customer Experience Lower TCO
- 90. MongoDB Solutions Big Data ContentMgmt & Delivery User Data Management 21 Mobile & Social Data Hub
- 91. MongoDB Partners (200+) Software& Services Cloud & Channel 22 Hardware
- 92. MongoDB Products andServices Subscriptions MongoDB Enterprise, MMS (On-Prem), Professional Support, Commercial License Consulting Expert Resources for All Phases of MongoDB Implementations Training Online and In-Person for Developers and Administrators MongoDB Management Service (MMS) Cloud-Based Suite of Services for Managing MongoDB Deployments 23
- 93. MongoDB Products andServices
- 94. MongoDB Enterprise Enterprise buildwith value-added capabilities • Advanced Security w/Kerberos • On-Prem Management – Visualization and alerts on 100+ system metrics – Backup features coming soon – On-premise version of MongoDB Monitoring Services (MMS) • Enterprise Software Integration via SNMP • Private, On-Demand MongoDB University Training • Certified OS Support 25
- 95. MongoDB Management Service Cloud-basedsuite of services for managing MongoDB deployments • Monitoring, with charts, dashboards and alerts on 100+ metrics • Backup and restore, with pointin-time recovery, support for sharded clusters • MMS On-Prem included with MongoDB Enterprise (backup coming soon) 26
- 96. Consulting Technical Account Manager Custom Consulting • Named MongoDB expert • Assist with all phases of project • Advisory services • E.g., config., testing, optimization, best practices • Ongoing basis Lightning Consults also available 27 Health Check • Assess overall status and health of existing MongoDB deployment
- 97. Training Public Private • Dev, admin,and combined courses available • North America and EMEA • Customized to your needs • For devs and admins • On-Site Online • Free • For devs and admins • 7 weeks • Weekly lectures, homework, final exam Private, On-Demand MongoDB University Training Included with MongoDB Enterprise Subscription 28
- 98. For More Information Resource MongoDBDownloads mongodb.com/download Free Online Training education.mongodb.com Webinars and Events mongodb.com/events White Papers mongodb.com/white-papers Case Studies mongodb.com/customers Presentations mongodb.com/presentations Documentation docs.mongodb.org Additional Info 29 Location [email protected]
- 99.