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LOGO du client

Big Data
à l’épreuve des projets d’entreprise
#2013
Bretagne 2013
Pas tout à fait….
Et des camions il y en a ….
Et des camions il y en a ….
Ecotaxe
§ Flux entrant 24/7
• 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
Big Data ?
Big Data
Règle des 3V
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
Big Data
Règle des 3V
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
Data
Toujours plus…

Quantité
de données

Temps
Toujours plus, et plus encore…

Quantité
de données

Temps
The Inverted U

Qualité de
décision

Peter Morville

Sous information

Sur information

Quantité d’informations

U

U/
Créer du
sens
Data è Information

Pour créer du sens
il faut
transformer la donnée en information
métadonnées

Donnée
propriétés
Exemple : individu, événement,
équipement
métadonnées

Exemple : tags, chronologie, géolocalisation,
relations, notes, commentaires….

Métadonnées
Donnée
propriétés
Information

Métadonnées
Donnée
propriétés
Cycle de création

Information
Data …………………………………………….......
Méta - Information

Création

Enrichissement

timeline
Rechercher / Représenter
Dan Roam
Rechercher / Représenter

#FacettedSearch
Trajectoire

Stocker

Rechercher

Analyser
Trajectoire

Stocker

Rechercher

Analyser
Trajectoire

Stocker

Rechercher

Analyser
Ecotaxe
Stocker

Rechercher

Analyser
Ecotaxe
§ Flux entrant 24/7
• 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
Architecture

#MongoDB
#Cluster
#Sharding
#Multi-sites
RETEX MongoDB

Changement de paradigme
§ 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
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
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
Vertical / Horizontal
« Scalabilité» Horizontale
Si besoin de plus de puissance
• on ajoute des serveurs
Corollaire : linéarisation du coût / usage
Vertical / Horizontal
« Scalabilité» Horizontale
Si besoin de plus de puissance
• on ajoute des serveurs
Corollaire : linéarisation du coût / usage
MongoDB
Ne pas utilisez MongoDB 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
SPARK
Stocker

Rechercher

Analyser
RETEX Elasticsearch

CQRS
Command Query Responsibility Segregation

Command

Query

Store

Index

EventBus
Stocker

Rechercher

Analyser

Rubedo
Le CMS Big Data
RETEX Rubedo
Premier CMS open-source
basé sur un socle NoSQL
+

Dans un monde où
LAMP est LA Norme

NoSQL, mais pour quoi faire ?
NoSQL et Gestion de contenus
§ Les CMS gèrent des Contenus …

… structurés
et
classés
Rubedo : comparaison des 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
Rubedo : les atouts 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)
Rubedo : les cas 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
RUBEDO : démonstration

NoSQL

JavaScript,
HTML5,
CS
CSS3

DEMONSTRATION
Pause

10 min
LOGO du client

Merci de votre attention
Elasticsearch
Revolutionizing Data Search
and Analytics
Richard Maurer– SEMEA Territory Manager
Agenda
•  Purpose of Elasticsearch
•  Features of Product
•  Customer Examples
•  Company Overview
•  Commercial Offerings
•  Resources
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
Features of Elasticsearch
•  Structured & unstructured search
•  Advanced analytics capabilities
•  Unmatched performance
•  Real-time results
•  Highly scalable
•  User friendly installation and maintenance
User: GitHub
Searches 20TB of data, 1.3 billion files and 130 lines
of code using Elasticsearch
User: Foursquare
Searches 50,000,000 venues every day using
Elasticsearch
User: Fog Creek Software
Searches 40,000,000,000 (40 billion) lines of code in
real-time using Elasticsearch
User: StumbleUpon
Delivers millions of recommendations every day
using Elasticsearch
Example: Email Archiving
Email Archiving of 2 Petabytes of data across 100’s of servers
Big data, structured and unstructured
Example: Support Agents
Custom Support – Search, Facets, and Reports
Real time metrics
Unprecedented Uptake
Elasticsearch has more than 5 Million downloads
… and 400,000 more each month

Cumulative
Cumulative
m
Company Overview
More than 5 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
Users
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.
Product Offerings:
Support Throughout Your Project
1.  Core Elasticsearch Training
2.  Development and Production Support
3.  Technical Account Manager
1: Training
Core Elasticsearch Training
•  Two day classroom training
•  Delivered by Elasticsearch developers
1.  Worldwide Public Courses
2.  Onsite Training Course
2: Support
3: Technical Account Manager
• 
• 
• 
• 
• 

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
Resources
•  www.elasticsearch.com
•  www.elasticsearch.org
•  User Groups:
http://www.elasticsearch.org/community/forum/
•  Contact:
Richard Maurer
Territory Manager
Richard.maurer@elasticsearch.com
Le Big Data à l'épreuve des
projets d'entreprise

Yann Aubry
Regional Director
The Big Data Unknown
Top Big Data Challenges?
Translation?
Most struggle
to know what
Big Data is,
how to manage
it and who can
manage it

3

Source: Gartner
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
When To Use Hadoop, NoSQL
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
Consideration – Online vs. Offline
Online

•  Real-time
•  Low-latency
•  High availability
7

vs.

Offline

•  Long-running
•  High-Latency
•  Availability is lower priority
Consideration – Online vs. Offline
Online

8

vs.

Offline
MongoDB/NoSQL Is Good for!

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
Hadoop Is Good for!

Risk Modeling

Recommendation
Engine

Ad Targeting

Transaction
Analysis

Trade
Surveillance

Network Failure
Prediction

10

Churn Analysis

Search Quality

Data Lake
How To Use The Two Together?
Case Study
Insurance leader generates 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
Machine Learning

Ad-Serving

Algorithms
MongoDB
Connector for
Hadoop

• 
• 
• 
• 
• 

13

Catalogs and products
User profiles
Clicks
Views
Transactions

•  User segmentation
•  Recommendation engine
•  Prediction engine
MongoDB overview
MongoDB
The leading NoSQL database

General
Purpose

15

Document
Database

OpenSource
MongoDB Vision
To provide the 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
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
Global Community
5,000,000+
MongoDB Downloads

100,000+
Online Education Registrants

20,000+
MongoDB User Group Members

20,000+
MongoDB Days Attendees

20,000+
MongoDB Management Service (MMS) Users

18
MongoDB Features
• JSON Document 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
MongoDB Business Value

Enabling New Apps

Faster Time to Market
20

Better Customer Experience

Lower TCO
MongoDB Solutions
Big Data

Content Mgmt & Delivery

User Data Management

21

Mobile & Social

Data Hub
MongoDB Partners (200+)
Software & Services

Cloud & Channel

22

Hardware
MongoDB Products and Services
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
MongoDB Products and Services
MongoDB Enterprise
Enterprise build with 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
MongoDB Management Service
Cloud-based suite 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
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
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
For More Information
Resource
MongoDB Downloads

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

info@mongodb.com
@yannaubry

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Le big data à l'épreuve des projets d'entreprise

  • 1. LOGO du client Big Data à l’épreuve des projets d’entreprise #2013
  • 3. Pas tout à fait….
  • 4.
  • 5.
  • 6.
  • 7. Et des camions il y en a ….
  • 8. Et des camions il y en a ….
  • 9. Ecotaxe § Flux entrant 24/7 • 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
  • 11. Big Data Règle des 3V 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 des 3V 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
  • 13. Data
  • 15. Toujours plus, et plus encore… Quantité de données Temps
  • 16. The Inverted U Qualité de décision Peter Morville Sous information Sur information Quantité d’informations U U/
  • 18. Data è Information Pour créer du sens il faut transformer la donnée en information
  • 20. métadonnées Exemple : tags, chronologie, géolocalisation, relations, notes, commentaires…. Métadonnées Donnée propriétés
  • 22. Cycle de création Information Data ……………………………………………....... Méta - Information Création Enrichissement timeline
  • 29. Ecotaxe § Flux entrant 24/7 • 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
  • 31. RETEX MongoDB Changement de paradigme § 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 utilisez MongoDB 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
  • 38.
  • 39.
  • 40.
  • 41. RETEX Elasticsearch CQRS Command Query Responsibility Segregation Command Query Store Index EventBus
  • 43. RETEX Rubedo Premier CMS open-source basé sur un socle NoSQL + Dans un monde où LAMP est LA Norme NoSQL, mais pour quoi faire ?
  • 44. NoSQL et Gestion de contenus § Les CMS gèrent des Contenus … … structurés et classés
  • 45. Rubedo : comparaison des 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 : les atouts 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 : les cas 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
  • 50. LOGO du client Merci de votre attention
  • 51. Elasticsearch Revolutionizing Data Search and Analytics Richard Maurer– SEMEA Territory Manager
  • 52. Agenda •  Purpose of Elasticsearch •  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 20TB of data, 1.3 billion files and 130 lines of code using Elasticsearch
  • 56. User: Foursquare Searches 50,000,000 venues every day using Elasticsearch
  • 57. User: Fog Creek Software Searches 40,000,000,000 (40 billion) lines of code in real-time using Elasticsearch
  • 58. User: StumbleUpon Delivers millions of recommendations every day using Elasticsearch
  • 59. Example: Email Archiving Email Archiving of 2 Petabytes of data across 100’s of servers Big data, structured and unstructured
  • 60. Example: Support Agents Custom Support – Search, Facets, and Reports Real time metrics
  • 61. Unprecedented Uptake Elasticsearch has more than 5 Million downloads … and 400,000 more each month Cumulative Cumulative m
  • 62. Company Overview More than 5 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
  • 63. Users
  • 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 Throughout Your Project 1.  Core Elasticsearch Training 2.  Development and Production Support 3.  Technical Account Manager
  • 66. 1: Training Core Elasticsearch Training •  Two day classroom training •  Delivered by Elasticsearch developers 1.  Worldwide Public Courses 2.  Onsite Training Course
  • 68. 3: Technical Account Manager •  •  •  •  •  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 Richard.maurer@elasticsearch.com
  • 70. Le Big Data à l'épreuve des projets d'entreprise Yann Aubry Regional Director
  • 71. The Big Data Unknown
  • 72. Top Big Data Challenges? 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 Use Hadoop, 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 – Online vs. Offline Online •  Real-time •  Low-latency •  High availability 7 vs. Offline •  Long-running •  High-Latency •  Availability is lower priority
  • 77. Consideration – Online vs. Offline Online 8 vs. Offline
  • 78. MongoDB/NoSQL Is Good for! 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 Good for! Risk Modeling Recommendation Engine Ad Targeting Transaction Analysis Trade Surveillance Network Failure Prediction 10 Churn Analysis Search Quality Data Lake
  • 80. How To Use The Two Together?
  • 81. Case Study Insurance leader generates 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 Catalogs and products User profiles Clicks Views Transactions •  User segmentation •  Recommendation engine •  Prediction engine
  • 84. MongoDB The leading NoSQL database General Purpose 15 Document Database OpenSource
  • 85. MongoDB Vision To provide the 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+ Online Education Registrants 20,000+ MongoDB User Group Members 20,000+ MongoDB Days Attendees 20,000+ MongoDB Management Service (MMS) Users 18
  • 88. MongoDB Features • JSON Document 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 Enabling New Apps Faster Time to Market 20 Better Customer Experience Lower TCO
  • 90. MongoDB Solutions Big Data Content Mgmt & Delivery User Data Management 21 Mobile & Social Data Hub
  • 91. MongoDB Partners (200+) Software & Services Cloud & Channel 22 Hardware
  • 92. MongoDB Products and Services 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
  • 94. MongoDB Enterprise Enterprise build with 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-based suite 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 MongoDB Downloads 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 info@mongodb.com