SlideShare une entreprise Scribd logo
1  sur  19
Predictive Analytics Leads to Successful
Recommendations and Direct Revenue Maximization
Christos Tryfonas, Ph.D.
CTO, Cloud & Big Data Analytics
                                                               INSTANT INTELLIGENCE




Web:	
  www.cetas.net	
  
Twi)er:	
  @CetasAnaly/cs	
  
Blog:	
  www.cetas.net/blog	
  
YouTube:	
  www.youtube.com/CetasAnaly/cs	
  
                                                © 2009 VMware Inc. All rights reserved
INSTANT INTELLIGENCE




      Transform IT
          + Transform Business
              + Transform Yourself



      Leverage Cetas to Transform
    Real-Time and Predictive Analytics

2
Infrastructure, Apps and now Data…                           INSTANT INTELLIGENCE




                             Build     Run
     Private
               Public
                            Analyze   Manage




Simplify Infrastructure   Simplify App Platform   Simplify Data
     With Cloud              Through PaaS             with
        (IaaS)                                      Analytics
                                                  as-a-Service


 3
Trend: New Data Growing at 60% Y/Y                                                                          INSTANT INTELLIGENCE




Exabytes of information stored                                                              20 Zetta by 2015

                                                                                            1 Yotta by 2030

                                                                                            Yes, you are part
                                                                                            of the yotta
                                                                          audio	
           generation…
                                                                 digital	
  tv	
  
                                                             digital	
  photos	
  
                                                  camera	
  phones,	
  rfid	
  
                                            medical	
  imaging,	
  sensors	
  
                     satellite	
  images,	
  logs,	
  scanners,	
  twi)er	
  
       cad/cam,	
  appliances,	
  machine	
  data,	
  digital	
  movies	
  



                                                                             Source: The Information Explosion, 2009


4
Data Growth in the Enterprise   INSTANT INTELLIGENCE




5
Trend: Value from Data Exceeds Hardware Cost                           INSTANT INTELLIGENCE




§  Value from the intelligence of data analytics now outstrips the cost
     of hardware
     •  Hadoop enables the use of 10x lower cost hardware
     •  Hardware cost halving every 18 months
                                                            Value
                    Big Iron:
                    $40k/CPU

                                                                    Commodity
                                                                    Cluster:
                                                                    $1k/CPU
                                          Cost




 6
The Big Data Problem                                              INSTANT INTELLIGENCE




    Velocity            Volume              Variety         Value


                                                              $

 10’s of Billions   From Terabytes to   Multi-Structured   Business
of Daily Records        Petabytes                          Insights




7
Trend: Big Data Analytics – Driven by Real-World Benefit   INSTANT INTELLIGENCE




8
Big Data Use Cases   INSTANT INTELLIGENCE




9
Big Data Analytics ROI                                                                                  INSTANT INTELLIGENCE




Source: Nucleus Research
http://www.enterpriseappstoday.com/business-intelligence/the-more-pervasive-business-analytics-roi-big-data.html

   10
Big Data Technology Stack   INSTANT INTELLIGENCE




11
A Holistic View of a Big Data System                                     INSTANT INTELLIGENCE




                Real-Time
                 Streams


                       Real-Time
                       Processing
                                           Analytics
Ingestion
    &                                      Big Query,
   ETL                      Real Time
                                            Search,           Batch
                            Database
                             (HBase,         Index          Processing
                            Cassandra)    (Google, Spunk,
                                              Cetas)




                            Unstructured Data (HDFS)



12
The Unified Analytics Cloud Platform                                         INSTANT INTELLIGENCE




          Mahout      R                                       Cetas/VMware
                               Analytics Tools
              Splunk                                  SAS or IBM SPSS

         Map Reduce              Developer           Spring
                                                                 PaaS
                 Python         Frameworks       Cloud Foundry

        Cassandra                                      HBase
                    HDFS     Database/DataStores
                 Greenplum                               Voldemort

        Hadoop
                                Data Platform           Data PaaS
            VMware /Cetas



             vSphere         Cloud Infrastructure
                                                       Private
                                                                   Public




13
A Unified Analytics Cloud Significantly Simplifies Infrastructure                  INSTANT INTELLIGENCE




                                   §  Simplify
                                       •  Single Hardware Infrastructure
                                       •  Faster/Easier provisioning
SQL or NoSQL Cluster




                                      Big SQL       NoSQL        Hadoop        Analytics
                                                                                Engine
      Analytics L Cluster


                                                Unified Analytics Infrastructure

                                                     Private
                                                               Public
 Hadoop Cluster

                                    §  Optimize
                                        •  Shared Resources = higher utilization
        Decision Support Cluster
                                        •  Elastic resources = faster on-demand
                                           access
 14
Predictive Analytics Objectives                    INSTANT INTELLIGENCE




§  Optimization of one or more target functions
  •  Example: Increase Customer Engagement
§  Vertical Specific
  •  Increase Customer Satisfaction
  •  Maximize Customer/User Engagement
  •  Minimize Churn Rate
  •  Maximize Revenue




15
Sample Applications of Predictive Analytics                        INSTANT INTELLIGENCE




§  eCommerce
    •  Customer interaction
    •  Revenue Maximization        Statistical /
    •  Inventory management       Regression
§  Mobile                           Models
    •  Capacity Planning
§  Ad/Publishing
    •  Ad serving                                Machine
    •  Customer Retention Management             Learning
                                               (NN, Bayesian,
§  Gaming                                          etc.)
    •  Ad serving
    •  Virtual Good Placement
    •  In-App Purchasing
                                                            Social Graph
§  IT
                                                              Algorithms
    •  Capacity Planning
    •  Alerting and Diagnosis

16
Taking Predictive Analytics to logical conclusion                          INSTANT INTELLIGENCE




§  Currently predictive analytics is in Silos
  •  Data Scientists w/ SAS, SPSS, Custom models
  •  Localized/Sampled Datasets
  •  Building Models using Open Source Modeling Tools: Hadoop, Mahout, R
§  Actionable Analytics
  •  Recommendation Engines (Examples: Amazon, Netflix)
  •  Product Placement Engines
  •  Targeted Ad Placement Engines
§  Cloudification of Predictive Analytics
  •  Analytics-as-a-Service approach
  •  Big Data support
§  Overall Objectives
  •  Revenue Maximization
  •  Social Penetration and User Engagement
17
Data is Being Stretched                                                INSTANT INTELLIGENCE




                      Intelligent Data
                                 §  Analytics Apps and
                                     Algorithms
                                 §  Discovery, Visibility,
                                     Pattern Extraction




      Big Data                                          Fast Data
                                                   §  Streaming, real-time and
§  Petabytes vs.
                                                       Unpredictable
    Gigabytes
                                                   §  Mobile app proliferation
§  Democratize
    Analytics



                                         §  Non-structured data
                      Flexible Data      §  Developer productivity

 18
Summary                                        INSTANT INTELLIGENCE




§  Cloudification of Analytics is happening




§  Predictive Analytics follow the Big Data
  and Social Web App trends




§  Direct Impact in Monetization from
  Predictive Modeling and Analytics




19

Contenu connexe

Tendances

Exploring Big Data value for your business
Exploring Big Data value for your businessExploring Big Data value for your business
Exploring Big Data value for your businessAcunu
 
Introduction to Cloud computing and Big Data-Hadoop
Introduction to Cloud computing and  Big Data-HadoopIntroduction to Cloud computing and  Big Data-Hadoop
Introduction to Cloud computing and Big Data-HadoopNagarjuna D.N
 
Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...
Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...
Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...AlmereDataCapital
 
Big Data = Big Decisions
Big Data = Big DecisionsBig Data = Big Decisions
Big Data = Big DecisionsInnoTech
 
Big Data Real Time Analytics - A Facebook Case Study
Big Data Real Time Analytics - A Facebook Case StudyBig Data Real Time Analytics - A Facebook Case Study
Big Data Real Time Analytics - A Facebook Case StudyNati Shalom
 
The rise of “Big Data” on cloud computing
The rise of “Big Data” on cloud computingThe rise of “Big Data” on cloud computing
The rise of “Big Data” on cloud computingMinhazul Arefin
 
Introduction to Gruter and Gruter's BigData Platform
Introduction to Gruter and Gruter's BigData PlatformIntroduction to Gruter and Gruter's BigData Platform
Introduction to Gruter and Gruter's BigData PlatformGruter
 
データマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMar
データマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMarデータマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMar
データマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMarK T
 
Big data analytics, survey r.nabati
Big data analytics, survey r.nabatiBig data analytics, survey r.nabati
Big data analytics, survey r.nabatinabati
 
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr..."Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...Dataconomy Media
 
THE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUME
THE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUMETHE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUME
THE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUMEGigaom
 
"From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",...
"From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",..."From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",...
"From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",...Dataconomy Media
 
2012.04.26 big insights streams im forum2
2012.04.26 big insights streams im forum22012.04.26 big insights streams im forum2
2012.04.26 big insights streams im forum2Wilfried Hoge
 
Fosec2011 keynote address
Fosec2011 keynote addressFosec2011 keynote address
Fosec2011 keynote addressthreesixty
 
Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012
Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012
Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012Preferred Networks
 
The Future Of Big Data
The Future Of Big DataThe Future Of Big Data
The Future Of Big DataMatthew Dennis
 
Orbit GT Mobile Mapping Solutions
Orbit GT Mobile Mapping SolutionsOrbit GT Mobile Mapping Solutions
Orbit GT Mobile Mapping SolutionsPeter Bonne
 
Tech4Africa - Opportunities around Big Data
Tech4Africa - Opportunities around Big DataTech4Africa - Opportunities around Big Data
Tech4Africa - Opportunities around Big DataSteve Watt
 

Tendances (20)

Exploring Big Data value for your business
Exploring Big Data value for your businessExploring Big Data value for your business
Exploring Big Data value for your business
 
Introduction to Cloud computing and Big Data-Hadoop
Introduction to Cloud computing and  Big Data-HadoopIntroduction to Cloud computing and  Big Data-Hadoop
Introduction to Cloud computing and Big Data-Hadoop
 
Introduction to R for Data Mining
Introduction to R for Data MiningIntroduction to R for Data Mining
Introduction to R for Data Mining
 
Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...
Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...
Maurice Bouwhuis (SARA/Vancis) - Hoe big data te begrijpen door ze te visuali...
 
Big Data = Big Decisions
Big Data = Big DecisionsBig Data = Big Decisions
Big Data = Big Decisions
 
Big Data Real Time Analytics - A Facebook Case Study
Big Data Real Time Analytics - A Facebook Case StudyBig Data Real Time Analytics - A Facebook Case Study
Big Data Real Time Analytics - A Facebook Case Study
 
The rise of “Big Data” on cloud computing
The rise of “Big Data” on cloud computingThe rise of “Big Data” on cloud computing
The rise of “Big Data” on cloud computing
 
Introduction to Gruter and Gruter's BigData Platform
Introduction to Gruter and Gruter's BigData PlatformIntroduction to Gruter and Gruter's BigData Platform
Introduction to Gruter and Gruter's BigData Platform
 
データマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMar
データマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMarデータマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMar
データマネジメント今昔物語〜プロダクトの視点から見るカオスと進化 #TechMar
 
Big data analytics, survey r.nabati
Big data analytics, survey r.nabatiBig data analytics, survey r.nabati
Big data analytics, survey r.nabati
 
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr..."Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...
"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr...
 
THE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUME
THE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUMETHE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUME
THE 3V’S OF BIG DATA: VARIETY, VELOCITY, and VOLUME
 
"From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",...
"From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",..."From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",...
"From Big Data To Big Valuewith HPE Predictive Analytics & Machine Learning",...
 
2012.04.26 big insights streams im forum2
2012.04.26 big insights streams im forum22012.04.26 big insights streams im forum2
2012.04.26 big insights streams im forum2
 
Fosec2011 keynote address
Fosec2011 keynote addressFosec2011 keynote address
Fosec2011 keynote address
 
Infochimps + CloudCon: Infinite Monkey Theorem
Infochimps + CloudCon: Infinite Monkey TheoremInfochimps + CloudCon: Infinite Monkey Theorem
Infochimps + CloudCon: Infinite Monkey Theorem
 
Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012
Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012
Jubatus: Realtime deep analytics for BIgData@Rakuten Technology Conference 2012
 
The Future Of Big Data
The Future Of Big DataThe Future Of Big Data
The Future Of Big Data
 
Orbit GT Mobile Mapping Solutions
Orbit GT Mobile Mapping SolutionsOrbit GT Mobile Mapping Solutions
Orbit GT Mobile Mapping Solutions
 
Tech4Africa - Opportunities around Big Data
Tech4Africa - Opportunities around Big DataTech4Africa - Opportunities around Big Data
Tech4Africa - Opportunities around Big Data
 

En vedette

The role of Dataset in training ANFIS System for Course Advisor
The role of Dataset in training ANFIS System for Course AdvisorThe role of Dataset in training ANFIS System for Course Advisor
The role of Dataset in training ANFIS System for Course AdvisorAM Publications
 
مذكرة رياضيات للصف الخامس الإبتدائي
مذكرة رياضيات للصف الخامس الإبتدائي مذكرة رياضيات للصف الخامس الإبتدائي
مذكرة رياضيات للصف الخامس الإبتدائي Abdallah Omar
 
Truman Transcript.compressed (1)
Truman Transcript.compressed (1)Truman Transcript.compressed (1)
Truman Transcript.compressed (1)David Atkinson
 
Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...
Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...
Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...AM Publications
 
Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...
Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...
Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...AssociationAMKO
 
4Service Group презентация о компании_2016
4Service Group презентация о компании_20164Service Group презентация о компании_2016
4Service Group презентация о компании_20164Service Group
 
Learn how to_play_the_guitar
Learn how to_play_the_guitarLearn how to_play_the_guitar
Learn how to_play_the_guitarcatherinehwng
 

En vedette (13)

The role of Dataset in training ANFIS System for Course Advisor
The role of Dataset in training ANFIS System for Course AdvisorThe role of Dataset in training ANFIS System for Course Advisor
The role of Dataset in training ANFIS System for Course Advisor
 
Pergolide 66104-22-1-api
Pergolide 66104-22-1-apiPergolide 66104-22-1-api
Pergolide 66104-22-1-api
 
priya resume
priya resumepriya resume
priya resume
 
Cetas Presentation at GigaOM Structure 2012
Cetas Presentation at GigaOM Structure 2012Cetas Presentation at GigaOM Structure 2012
Cetas Presentation at GigaOM Structure 2012
 
مذكرة رياضيات للصف الخامس الإبتدائي
مذكرة رياضيات للصف الخامس الإبتدائي مذكرة رياضيات للصف الخامس الإبتدائي
مذكرة رياضيات للصف الخامس الإبتدائي
 
Truman Transcript.compressed (1)
Truman Transcript.compressed (1)Truman Transcript.compressed (1)
Truman Transcript.compressed (1)
 
Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...
Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...
Anticorrosive Activity of Rosemarinus officinalis L. Leaves Extract Against M...
 
Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...
Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...
Внедрение Мистери шоппинг: как с минимальными затратами донести эффективность...
 
Bally
BallyBally
Bally
 
Telenor
TelenorTelenor
Telenor
 
4Service Group презентация о компании_2016
4Service Group презентация о компании_20164Service Group презентация о компании_2016
4Service Group презентация о компании_2016
 
resume saeedi
resume saeediresume saeedi
resume saeedi
 
Learn how to_play_the_guitar
Learn how to_play_the_guitarLearn how to_play_the_guitar
Learn how to_play_the_guitar
 

Similaire à Cetas Predictive Analytics Prezo

Architecting Virtualized Infrastructure for Big Data
Architecting Virtualized Infrastructure for Big DataArchitecting Virtualized Infrastructure for Big Data
Architecting Virtualized Infrastructure for Big DataRichard McDougall
 
Building Big Data Applications
Building Big Data ApplicationsBuilding Big Data Applications
Building Big Data ApplicationsRichard McDougall
 
Big Data and Implications on Platform Architecture
Big Data and Implications on Platform ArchitectureBig Data and Implications on Platform Architecture
Big Data and Implications on Platform ArchitectureOdinot Stanislas
 
Big Data, Big Content, and Aligning Your Storage Strategy
Big Data, Big Content, and Aligning Your Storage StrategyBig Data, Big Content, and Aligning Your Storage Strategy
Big Data, Big Content, and Aligning Your Storage StrategyHitachi Vantara
 
Big Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the FutureBig Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the FutureOdinot Stanislas
 
Big Data launch keynote Singapore Patrick Buddenbaum
Big Data launch keynote Singapore Patrick BuddenbaumBig Data launch keynote Singapore Patrick Buddenbaum
Big Data launch keynote Singapore Patrick BuddenbaumIntelAPAC
 
Big Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure ConsiderationsBig Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure ConsiderationsRichard McDougall
 
Apache hadoop bigdata-in-banking
Apache hadoop bigdata-in-bankingApache hadoop bigdata-in-banking
Apache hadoop bigdata-in-bankingm_hepburn
 
Introduction to Big Data An analogy between Sugar Cane & Big Data
Introduction to Big Data An analogy  between Sugar Cane & Big DataIntroduction to Big Data An analogy  between Sugar Cane & Big Data
Introduction to Big Data An analogy between Sugar Cane & Big DataJean-Marc Desvaux
 
Big Data, Simple and Fast: Addressing the Shortcomings of Hadoop
Big Data, Simple and Fast: Addressing the Shortcomings of HadoopBig Data, Simple and Fast: Addressing the Shortcomings of Hadoop
Big Data, Simple and Fast: Addressing the Shortcomings of HadoopHazelcast
 
Hitachi Data Systems Big Data Roadmap
Hitachi Data Systems Big Data RoadmapHitachi Data Systems Big Data Roadmap
Hitachi Data Systems Big Data RoadmapHitachi Vantara
 
Presentation architecting virtualized infrastructure for big data
Presentation   architecting virtualized infrastructure for big dataPresentation   architecting virtualized infrastructure for big data
Presentation architecting virtualized infrastructure for big datasolarisyourep
 
Presentation architecting virtualized infrastructure for big data
Presentation   architecting virtualized infrastructure for big dataPresentation   architecting virtualized infrastructure for big data
Presentation architecting virtualized infrastructure for big dataxKinAnx
 
Big data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You WantBig data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You WantStuart Miniman
 
Don't be Hadooped when looking for Big Data ROI
Don't be Hadooped when looking for Big Data ROIDon't be Hadooped when looking for Big Data ROI
Don't be Hadooped when looking for Big Data ROIDataWorks Summit
 
Davis mark advanced search analytics in 20 minutes
Davis mark   advanced search analytics in 20 minutesDavis mark   advanced search analytics in 20 minutes
Davis mark advanced search analytics in 20 minutesLucidworks (Archived)
 
Architecting virtualized infrastructure for big data presentation
Architecting virtualized infrastructure for big data presentationArchitecting virtualized infrastructure for big data presentation
Architecting virtualized infrastructure for big data presentationVlad Ponomarev
 
Big Data launch Singapore Patrick Buddenbaum
Big Data launch Singapore Patrick BuddenbaumBig Data launch Singapore Patrick Buddenbaum
Big Data launch Singapore Patrick BuddenbaumIntelAPAC
 
Ibm big data hadoop summit 2012 james kobielus final 6-13-12(1)
Ibm big data    hadoop summit 2012 james kobielus final 6-13-12(1)Ibm big data    hadoop summit 2012 james kobielus final 6-13-12(1)
Ibm big data hadoop summit 2012 james kobielus final 6-13-12(1)Ajay Ohri
 

Similaire à Cetas Predictive Analytics Prezo (20)

Architecting Virtualized Infrastructure for Big Data
Architecting Virtualized Infrastructure for Big DataArchitecting Virtualized Infrastructure for Big Data
Architecting Virtualized Infrastructure for Big Data
 
Building Big Data Applications
Building Big Data ApplicationsBuilding Big Data Applications
Building Big Data Applications
 
Big Data and Implications on Platform Architecture
Big Data and Implications on Platform ArchitectureBig Data and Implications on Platform Architecture
Big Data and Implications on Platform Architecture
 
Big Data, Big Content, and Aligning Your Storage Strategy
Big Data, Big Content, and Aligning Your Storage StrategyBig Data, Big Content, and Aligning Your Storage Strategy
Big Data, Big Content, and Aligning Your Storage Strategy
 
Big Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the FutureBig Data Beyond Hadoop*: Research Directions for the Future
Big Data Beyond Hadoop*: Research Directions for the Future
 
Big Data launch keynote Singapore Patrick Buddenbaum
Big Data launch keynote Singapore Patrick BuddenbaumBig Data launch keynote Singapore Patrick Buddenbaum
Big Data launch keynote Singapore Patrick Buddenbaum
 
Big Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure ConsiderationsBig Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure Considerations
 
Introducing Splunk – The Big Data Engine
Introducing Splunk – The Big Data EngineIntroducing Splunk – The Big Data Engine
Introducing Splunk – The Big Data Engine
 
Apache hadoop bigdata-in-banking
Apache hadoop bigdata-in-bankingApache hadoop bigdata-in-banking
Apache hadoop bigdata-in-banking
 
Introduction to Big Data An analogy between Sugar Cane & Big Data
Introduction to Big Data An analogy  between Sugar Cane & Big DataIntroduction to Big Data An analogy  between Sugar Cane & Big Data
Introduction to Big Data An analogy between Sugar Cane & Big Data
 
Big Data, Simple and Fast: Addressing the Shortcomings of Hadoop
Big Data, Simple and Fast: Addressing the Shortcomings of HadoopBig Data, Simple and Fast: Addressing the Shortcomings of Hadoop
Big Data, Simple and Fast: Addressing the Shortcomings of Hadoop
 
Hitachi Data Systems Big Data Roadmap
Hitachi Data Systems Big Data RoadmapHitachi Data Systems Big Data Roadmap
Hitachi Data Systems Big Data Roadmap
 
Presentation architecting virtualized infrastructure for big data
Presentation   architecting virtualized infrastructure for big dataPresentation   architecting virtualized infrastructure for big data
Presentation architecting virtualized infrastructure for big data
 
Presentation architecting virtualized infrastructure for big data
Presentation   architecting virtualized infrastructure for big dataPresentation   architecting virtualized infrastructure for big data
Presentation architecting virtualized infrastructure for big data
 
Big data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You WantBig data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You Want
 
Don't be Hadooped when looking for Big Data ROI
Don't be Hadooped when looking for Big Data ROIDon't be Hadooped when looking for Big Data ROI
Don't be Hadooped when looking for Big Data ROI
 
Davis mark advanced search analytics in 20 minutes
Davis mark   advanced search analytics in 20 minutesDavis mark   advanced search analytics in 20 minutes
Davis mark advanced search analytics in 20 minutes
 
Architecting virtualized infrastructure for big data presentation
Architecting virtualized infrastructure for big data presentationArchitecting virtualized infrastructure for big data presentation
Architecting virtualized infrastructure for big data presentation
 
Big Data launch Singapore Patrick Buddenbaum
Big Data launch Singapore Patrick BuddenbaumBig Data launch Singapore Patrick Buddenbaum
Big Data launch Singapore Patrick Buddenbaum
 
Ibm big data hadoop summit 2012 james kobielus final 6-13-12(1)
Ibm big data    hadoop summit 2012 james kobielus final 6-13-12(1)Ibm big data    hadoop summit 2012 james kobielus final 6-13-12(1)
Ibm big data hadoop summit 2012 james kobielus final 6-13-12(1)
 

Plus de Pivotal Analytics (Cetas Analytics)

Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...
Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...
Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...Pivotal Analytics (Cetas Analytics)
 
Real-Time Customer Intelligence: The New Heartbeat for Growth and Profitability
Real-Time Customer Intelligence: The New Heartbeat for Growth and ProfitabilityReal-Time Customer Intelligence: The New Heartbeat for Growth and Profitability
Real-Time Customer Intelligence: The New Heartbeat for Growth and ProfitabilityPivotal Analytics (Cetas Analytics)
 
Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...
Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...
Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...Pivotal Analytics (Cetas Analytics)
 
Laura Madsen Healthcare Business Intelligence & Big Data Analytics
Laura Madsen Healthcare Business Intelligence & Big Data AnalyticsLaura Madsen Healthcare Business Intelligence & Big Data Analytics
Laura Madsen Healthcare Business Intelligence & Big Data AnalyticsPivotal Analytics (Cetas Analytics)
 

Plus de Pivotal Analytics (Cetas Analytics) (7)

Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...
Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...
Gamification: Leveraging Game Strategies & Big Data to Drive Business with Dr...
 
Dr. Bob Hayes Big Data and the Total Customer Experience
Dr. Bob Hayes Big Data and the Total Customer ExperienceDr. Bob Hayes Big Data and the Total Customer Experience
Dr. Bob Hayes Big Data and the Total Customer Experience
 
Real-Time Customer Intelligence: The New Heartbeat for Growth and Profitability
Real-Time Customer Intelligence: The New Heartbeat for Growth and ProfitabilityReal-Time Customer Intelligence: The New Heartbeat for Growth and Profitability
Real-Time Customer Intelligence: The New Heartbeat for Growth and Profitability
 
Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...
Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...
Streaming Cloud Analytics: Enabling Dynamic Product Innovation From User Expe...
 
Wayne Eckerson: Secrets of Analytical Leaders
Wayne Eckerson: Secrets of Analytical LeadersWayne Eckerson: Secrets of Analytical Leaders
Wayne Eckerson: Secrets of Analytical Leaders
 
Laura Madsen Healthcare Business Intelligence & Big Data Analytics
Laura Madsen Healthcare Business Intelligence & Big Data AnalyticsLaura Madsen Healthcare Business Intelligence & Big Data Analytics
Laura Madsen Healthcare Business Intelligence & Big Data Analytics
 
Cetas Presentation on Real-time Recommendation Systems
Cetas Presentation on Real-time Recommendation SystemsCetas Presentation on Real-time Recommendation Systems
Cetas Presentation on Real-time Recommendation Systems
 

Dernier

Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfOrbitshub
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Orbitshub
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWERMadyBayot
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodJuan lago vázquez
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsNanddeep Nachan
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...apidays
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businesspanagenda
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...apidays
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesrafiqahmad00786416
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoffsammart93
 

Dernier (20)

Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 

Cetas Predictive Analytics Prezo

  • 1. Predictive Analytics Leads to Successful Recommendations and Direct Revenue Maximization Christos Tryfonas, Ph.D. CTO, Cloud & Big Data Analytics INSTANT INTELLIGENCE Web:  www.cetas.net   Twi)er:  @CetasAnaly/cs   Blog:  www.cetas.net/blog   YouTube:  www.youtube.com/CetasAnaly/cs   © 2009 VMware Inc. All rights reserved
  • 2. INSTANT INTELLIGENCE Transform IT + Transform Business + Transform Yourself Leverage Cetas to Transform Real-Time and Predictive Analytics 2
  • 3. Infrastructure, Apps and now Data… INSTANT INTELLIGENCE Build Run Private Public Analyze Manage Simplify Infrastructure Simplify App Platform Simplify Data With Cloud Through PaaS with (IaaS) Analytics as-a-Service 3
  • 4. Trend: New Data Growing at 60% Y/Y INSTANT INTELLIGENCE Exabytes of information stored 20 Zetta by 2015 1 Yotta by 2030 Yes, you are part of the yotta audio   generation… digital  tv   digital  photos   camera  phones,  rfid   medical  imaging,  sensors   satellite  images,  logs,  scanners,  twi)er   cad/cam,  appliances,  machine  data,  digital  movies   Source: The Information Explosion, 2009 4
  • 5. Data Growth in the Enterprise INSTANT INTELLIGENCE 5
  • 6. Trend: Value from Data Exceeds Hardware Cost INSTANT INTELLIGENCE §  Value from the intelligence of data analytics now outstrips the cost of hardware •  Hadoop enables the use of 10x lower cost hardware •  Hardware cost halving every 18 months Value Big Iron: $40k/CPU Commodity Cluster: $1k/CPU Cost 6
  • 7. The Big Data Problem INSTANT INTELLIGENCE Velocity Volume Variety Value $ 10’s of Billions From Terabytes to Multi-Structured Business of Daily Records Petabytes Insights 7
  • 8. Trend: Big Data Analytics – Driven by Real-World Benefit INSTANT INTELLIGENCE 8
  • 9. Big Data Use Cases INSTANT INTELLIGENCE 9
  • 10. Big Data Analytics ROI INSTANT INTELLIGENCE Source: Nucleus Research http://www.enterpriseappstoday.com/business-intelligence/the-more-pervasive-business-analytics-roi-big-data.html 10
  • 11. Big Data Technology Stack INSTANT INTELLIGENCE 11
  • 12. A Holistic View of a Big Data System INSTANT INTELLIGENCE Real-Time Streams Real-Time Processing Analytics Ingestion & Big Query, ETL Real Time Search, Batch Database (HBase, Index Processing Cassandra) (Google, Spunk, Cetas) Unstructured Data (HDFS) 12
  • 13. The Unified Analytics Cloud Platform INSTANT INTELLIGENCE Mahout R Cetas/VMware Analytics Tools Splunk SAS or IBM SPSS Map Reduce Developer Spring PaaS Python Frameworks Cloud Foundry Cassandra HBase HDFS Database/DataStores Greenplum Voldemort Hadoop Data Platform Data PaaS VMware /Cetas vSphere Cloud Infrastructure Private Public 13
  • 14. A Unified Analytics Cloud Significantly Simplifies Infrastructure INSTANT INTELLIGENCE §  Simplify •  Single Hardware Infrastructure •  Faster/Easier provisioning SQL or NoSQL Cluster Big SQL NoSQL Hadoop Analytics Engine Analytics L Cluster Unified Analytics Infrastructure Private Public Hadoop Cluster §  Optimize •  Shared Resources = higher utilization Decision Support Cluster •  Elastic resources = faster on-demand access 14
  • 15. Predictive Analytics Objectives INSTANT INTELLIGENCE §  Optimization of one or more target functions •  Example: Increase Customer Engagement §  Vertical Specific •  Increase Customer Satisfaction •  Maximize Customer/User Engagement •  Minimize Churn Rate •  Maximize Revenue 15
  • 16. Sample Applications of Predictive Analytics INSTANT INTELLIGENCE §  eCommerce •  Customer interaction •  Revenue Maximization Statistical / •  Inventory management Regression §  Mobile Models •  Capacity Planning §  Ad/Publishing •  Ad serving Machine •  Customer Retention Management Learning (NN, Bayesian, §  Gaming etc.) •  Ad serving •  Virtual Good Placement •  In-App Purchasing Social Graph §  IT Algorithms •  Capacity Planning •  Alerting and Diagnosis 16
  • 17. Taking Predictive Analytics to logical conclusion INSTANT INTELLIGENCE §  Currently predictive analytics is in Silos •  Data Scientists w/ SAS, SPSS, Custom models •  Localized/Sampled Datasets •  Building Models using Open Source Modeling Tools: Hadoop, Mahout, R §  Actionable Analytics •  Recommendation Engines (Examples: Amazon, Netflix) •  Product Placement Engines •  Targeted Ad Placement Engines §  Cloudification of Predictive Analytics •  Analytics-as-a-Service approach •  Big Data support §  Overall Objectives •  Revenue Maximization •  Social Penetration and User Engagement 17
  • 18. Data is Being Stretched INSTANT INTELLIGENCE Intelligent Data §  Analytics Apps and Algorithms §  Discovery, Visibility, Pattern Extraction Big Data Fast Data §  Streaming, real-time and §  Petabytes vs. Unpredictable Gigabytes §  Mobile app proliferation §  Democratize Analytics §  Non-structured data Flexible Data §  Developer productivity 18
  • 19. Summary INSTANT INTELLIGENCE §  Cloudification of Analytics is happening §  Predictive Analytics follow the Big Data and Social Web App trends §  Direct Impact in Monetization from Predictive Modeling and Analytics 19