SlideShare una empresa de Scribd logo
1 de 21
Descargar para leer sin conexión
Machine learning
Big Data, Budapest V3.0
Gianluigi Vigano’
Fouad Teban
Budapest, HU
19th of May 2016
Use cases for Machine learning
– IoT
– Clickstream
– Predictive maintenance
– Data normalization
– Demand forecasting
– Cyber security
– Scoring
– Churn Analytics
– Social graph analysis
– Tickstore data cleanups
2
Motivations of Machine Learning inside RDBMS
Minimize the data movement
• No need to move the data out of the RDMS to other systems to train a model
• Run predictions in RDBMS, where the data is
A single system for SQL analytics and machine learning
A familiar interface for existing RDBMS users to do machine learning
3
Machine learning with HPE Vertica
Big Data, Budapest V3.0
Gianluigi Vigano’
Fouad Teban
Budapest, HU
19th of May 2016
HPE Vertica: No limits, no compromises.
Supports all preferred tools
Open architecture
50x-1,000x faster
Blazing fast analytics
Unlimited low-cost nodes
Massive scalability
10x-30x more data per server
Optimized data storage
Private Cloud Public Cloud ApplianceSoftware Only
Purpose built for Big Data - from the very first line of code
Flexible deployment
Vertica high performance
advanced analytics
 Real-time performance at Scale
 On Premise, Cloud and On
Demand
 Native optimized SQL on
Hadoop
IDOL augmented
intelligence for human
information
 Advanced enterprise search
and rich media analytics
 Analyze text, audio, image
and streaming video
Haven OnDemand APIs
and Services
 Machine Learning as a
Service
 Delivered on Microsoft Azure
Cloud
 Accessible to any developer
HPE IDOL

Más contenido relacionado

La actualidad más candente

La actualidad más candente (20)

Oracle NoSQL DB & InfiniteGraph - Trends in Big Data and Graph Technology
Oracle NoSQL DB & InfiniteGraph - Trends in Big Data and Graph TechnologyOracle NoSQL DB & InfiniteGraph - Trends in Big Data and Graph Technology
Oracle NoSQL DB & InfiniteGraph - Trends in Big Data and Graph Technology
 
Driving Datascience at scale using Postgresql, Greenplum and Dataiku - Greenp...
Driving Datascience at scale using Postgresql, Greenplum and Dataiku - Greenp...Driving Datascience at scale using Postgresql, Greenplum and Dataiku - Greenp...
Driving Datascience at scale using Postgresql, Greenplum and Dataiku - Greenp...
 
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data VirtualityBeyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
 
Big Data Projects Research Ideas
Big Data Projects Research IdeasBig Data Projects Research Ideas
Big Data Projects Research Ideas
 
What is Big Data ?
What is Big Data ?What is Big Data ?
What is Big Data ?
 
Big data Introduction
Big data IntroductionBig data Introduction
Big data Introduction
 
Data Analytics in Real World (May 2016)
Data Analytics in Real World (May 2016)Data Analytics in Real World (May 2016)
Data Analytics in Real World (May 2016)
 
Graphs in Telecommunications - Jesus Barrasa, Neo4j
Graphs in Telecommunications - Jesus Barrasa, Neo4jGraphs in Telecommunications - Jesus Barrasa, Neo4j
Graphs in Telecommunications - Jesus Barrasa, Neo4j
 
Big data
Big dataBig data
Big data
 
Self-Service Analytics with Guard Rails
Self-Service Analytics with Guard RailsSelf-Service Analytics with Guard Rails
Self-Service Analytics with Guard Rails
 
datavirtuality - Beyond the data lake
datavirtuality - Beyond the data lake  datavirtuality - Beyond the data lake
datavirtuality - Beyond the data lake
 
Sudhir Rawat, Sr Techonology Evangelist at Microsoft SQL Business Intelligenc...
Sudhir Rawat, Sr Techonology Evangelist at Microsoft SQL Business Intelligenc...Sudhir Rawat, Sr Techonology Evangelist at Microsoft SQL Business Intelligenc...
Sudhir Rawat, Sr Techonology Evangelist at Microsoft SQL Business Intelligenc...
 
Unified approach to analytics
Unified approach to analyticsUnified approach to analytics
Unified approach to analytics
 
"Social innovation with (big) data" - Maurice Fransen, Analytics Lead Public ...
"Social innovation with (big) data" - Maurice Fransen, Analytics Lead Public ..."Social innovation with (big) data" - Maurice Fransen, Analytics Lead Public ...
"Social innovation with (big) data" - Maurice Fransen, Analytics Lead Public ...
 
Building A Self Service Analytics Platform on Hadoop
Building A Self Service Analytics Platform on HadoopBuilding A Self Service Analytics Platform on Hadoop
Building A Self Service Analytics Platform on Hadoop
 
6 levels of big data analytics applications
6 levels of big data analytics applications6 levels of big data analytics applications
6 levels of big data analytics applications
 
How OpenTable uses Big Data to impact growth by Raman Marya
How OpenTable uses Big Data to impact growth by Raman MaryaHow OpenTable uses Big Data to impact growth by Raman Marya
How OpenTable uses Big Data to impact growth by Raman Marya
 
Big Data
Big DataBig Data
Big Data
 
Bigdata Analytics using Hadoop
Bigdata Analytics using HadoopBigdata Analytics using Hadoop
Bigdata Analytics using Hadoop
 
Pieter den Hamer Alliander
Pieter den Hamer Alliander Pieter den Hamer Alliander
Pieter den Hamer Alliander
 

Similar a Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager | Big Data Platform at HPE

Building Large-Scale Applications for the Internet of Things at Bosch
Building Large-Scale Applications for the Internet of Things at BoschBuilding Large-Scale Applications for the Internet of Things at Bosch
Building Large-Scale Applications for the Internet of Things at Bosch
MongoDB
 
Cloud and Bid data Dr.VK.pdf
Cloud and Bid data Dr.VK.pdfCloud and Bid data Dr.VK.pdf
Cloud and Bid data Dr.VK.pdf
kalai75
 

Similar a Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager | Big Data Platform at HPE (20)

Realtime stream analytics with momentum
Realtime stream analytics with momentumRealtime stream analytics with momentum
Realtime stream analytics with momentum
 
IoT meets Big Data
IoT meets Big DataIoT meets Big Data
IoT meets Big Data
 
Operational information processing: lightning-fast, delightfully simple
Operational information processing: lightning-fast, delightfully simpleOperational information processing: lightning-fast, delightfully simple
Operational information processing: lightning-fast, delightfully simple
 
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
 
Big Data Analytics for Real Time Systems
Big Data Analytics for Real Time SystemsBig Data Analytics for Real Time Systems
Big Data Analytics for Real Time Systems
 
Big Data : Risks and Opportunities
Big Data : Risks and OpportunitiesBig Data : Risks and Opportunities
Big Data : Risks and Opportunities
 
Building Large-Scale Applications for the Internet of Things at Bosch
Building Large-Scale Applications for the Internet of Things at BoschBuilding Large-Scale Applications for the Internet of Things at Bosch
Building Large-Scale Applications for the Internet of Things at Bosch
 
Making Actionable Decisions at the Network's Edge
Making Actionable Decisions at the Network's EdgeMaking Actionable Decisions at the Network's Edge
Making Actionable Decisions at the Network's Edge
 
General introduction to IoTCrawler
General introduction to IoTCrawlerGeneral introduction to IoTCrawler
General introduction to IoTCrawler
 
Leveraging a big data model in the IT domain
Leveraging a big data model in the IT domainLeveraging a big data model in the IT domain
Leveraging a big data model in the IT domain
 
Information Security Analytics
Information Security AnalyticsInformation Security Analytics
Information Security Analytics
 
Cloud and Bid data Dr.VK.pdf
Cloud and Bid data Dr.VK.pdfCloud and Bid data Dr.VK.pdf
Cloud and Bid data Dr.VK.pdf
 
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
 
Building a reliable and scalable IoT platform with MongoDB and HiveMQ
Building a reliable and scalable IoT platform with MongoDB and HiveMQBuilding a reliable and scalable IoT platform with MongoDB and HiveMQ
Building a reliable and scalable IoT platform with MongoDB and HiveMQ
 
inmation Presentation_2017
inmation Presentation_2017inmation Presentation_2017
inmation Presentation_2017
 
Data Virtualization: An Introduction
Data Virtualization: An IntroductionData Virtualization: An Introduction
Data Virtualization: An Introduction
 
Platform for Big Data Analytics and Visual Analytics: CSIRO use cases. Februa...
Platform for Big Data Analytics and Visual Analytics: CSIRO use cases. Februa...Platform for Big Data Analytics and Visual Analytics: CSIRO use cases. Februa...
Platform for Big Data Analytics and Visual Analytics: CSIRO use cases. Februa...
 
Accelerating Insight - Smart Data Lake Customer Success Stories
Accelerating Insight - Smart Data Lake Customer Success StoriesAccelerating Insight - Smart Data Lake Customer Success Stories
Accelerating Insight - Smart Data Lake Customer Success Stories
 
The Pandemic Changes Everything, the Need for Speed and Resiliency
The Pandemic Changes Everything, the Need for Speed and ResiliencyThe Pandemic Changes Everything, the Need for Speed and Resiliency
The Pandemic Changes Everything, the Need for Speed and Resiliency
 
BigData Analysis
BigData AnalysisBigData Analysis
BigData Analysis
 

Más de Dataconomy Media

Más de Dataconomy Media (20)

Data Natives Paris v 10.0 | "Blockchain in Healthcare" - Lea Dias & David An...
Data Natives Paris v 10.0 | "Blockchain in Healthcare" - Lea Dias & 	David An...Data Natives Paris v 10.0 | "Blockchain in Healthcare" - Lea Dias & 	David An...
Data Natives Paris v 10.0 | "Blockchain in Healthcare" - Lea Dias & David An...
 
Data Natives Frankfurt v 11.0 | "Competitive advantages with knowledge graphs...
Data Natives Frankfurt v 11.0 | "Competitive advantages with knowledge graphs...Data Natives Frankfurt v 11.0 | "Competitive advantages with knowledge graphs...
Data Natives Frankfurt v 11.0 | "Competitive advantages with knowledge graphs...
 
Data Natives Frankfurt v 11.0 | "Can we be responsible for misuse of data & a...
Data Natives Frankfurt v 11.0 | "Can we be responsible for misuse of data & a...Data Natives Frankfurt v 11.0 | "Can we be responsible for misuse of data & a...
Data Natives Frankfurt v 11.0 | "Can we be responsible for misuse of data & a...
 
Data Natives Munich v 12.0 | "How to be more productive with Autonomous Data ...
Data Natives Munich v 12.0 | "How to be more productive with Autonomous Data ...Data Natives Munich v 12.0 | "How to be more productive with Autonomous Data ...
Data Natives Munich v 12.0 | "How to be more productive with Autonomous Data ...
 
Data Natives meets DataRobot | "Build and deploy an anti-money laundering mo...
Data Natives meets DataRobot |  "Build and deploy an anti-money laundering mo...Data Natives meets DataRobot |  "Build and deploy an anti-money laundering mo...
Data Natives meets DataRobot | "Build and deploy an anti-money laundering mo...
 
Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, So...
Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, So...Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, So...
Data Natives Munich v 12.0 | "Political Data Science: A tale of Fake News, So...
 
Data Natives Vienna v 7.0 | "Building Kubernetes Operators with KUDO for Dat...
Data Natives Vienna v 7.0  | "Building Kubernetes Operators with KUDO for Dat...Data Natives Vienna v 7.0  | "Building Kubernetes Operators with KUDO for Dat...
Data Natives Vienna v 7.0 | "Building Kubernetes Operators with KUDO for Dat...
 
Data Natives Vienna v 7.0 | "The Ingredients of Data Innovation" - Robbert de...
Data Natives Vienna v 7.0 | "The Ingredients of Data Innovation" - Robbert de...Data Natives Vienna v 7.0 | "The Ingredients of Data Innovation" - Robbert de...
Data Natives Vienna v 7.0 | "The Ingredients of Data Innovation" - Robbert de...
 
Data Natives Cologne v 4.0 | "The Data Lorax: Planting the Seeds of Fairness...
Data Natives Cologne v 4.0  | "The Data Lorax: Planting the Seeds of Fairness...Data Natives Cologne v 4.0  | "The Data Lorax: Planting the Seeds of Fairness...
Data Natives Cologne v 4.0 | "The Data Lorax: Planting the Seeds of Fairness...
 
Data Natives Cologne v 4.0 | "How People Analytics Can Reveal the Hidden Aspe...
Data Natives Cologne v 4.0 | "How People Analytics Can Reveal the Hidden Aspe...Data Natives Cologne v 4.0 | "How People Analytics Can Reveal the Hidden Aspe...
Data Natives Cologne v 4.0 | "How People Analytics Can Reveal the Hidden Aspe...
 
Data Natives Amsterdam v 9.0 | "Ten Little Servers: A Story of no Downtime" -...
Data Natives Amsterdam v 9.0 | "Ten Little Servers: A Story of no Downtime" -...Data Natives Amsterdam v 9.0 | "Ten Little Servers: A Story of no Downtime" -...
Data Natives Amsterdam v 9.0 | "Ten Little Servers: A Story of no Downtime" -...
 
Data Natives Amsterdam v 9.0 | "Point in Time Labeling at Scale" - Timothy Th...
Data Natives Amsterdam v 9.0 | "Point in Time Labeling at Scale" - Timothy Th...Data Natives Amsterdam v 9.0 | "Point in Time Labeling at Scale" - Timothy Th...
Data Natives Amsterdam v 9.0 | "Point in Time Labeling at Scale" - Timothy Th...
 
Data Natives Hamburg v 6.0 | "Interpersonal behavior: observing Alex to under...
Data Natives Hamburg v 6.0 | "Interpersonal behavior: observing Alex to under...Data Natives Hamburg v 6.0 | "Interpersonal behavior: observing Alex to under...
Data Natives Hamburg v 6.0 | "Interpersonal behavior: observing Alex to under...
 
Data Natives Hamburg v 6.0 | "About Surfing, Failing & Scaling" - Florian Sch...
Data Natives Hamburg v 6.0 | "About Surfing, Failing & Scaling" - Florian Sch...Data Natives Hamburg v 6.0 | "About Surfing, Failing & Scaling" - Florian Sch...
Data Natives Hamburg v 6.0 | "About Surfing, Failing & Scaling" - Florian Sch...
 
Data NativesBerlin v 20.0 | "Serving A/B experimentation platform end-to-end"...
Data NativesBerlin v 20.0 | "Serving A/B experimentation platform end-to-end"...Data NativesBerlin v 20.0 | "Serving A/B experimentation platform end-to-end"...
Data NativesBerlin v 20.0 | "Serving A/B experimentation platform end-to-end"...
 
Data Natives Berlin v 20.0 | "Ten Little Servers: A Story of no Downtime" - A...
Data Natives Berlin v 20.0 | "Ten Little Servers: A Story of no Downtime" - A...Data Natives Berlin v 20.0 | "Ten Little Servers: A Story of no Downtime" - A...
Data Natives Berlin v 20.0 | "Ten Little Servers: A Story of no Downtime" - A...
 
Big Data Frankfurt meets Thinkport | "The Cloud as a Driver of Innovation" - ...
Big Data Frankfurt meets Thinkport | "The Cloud as a Driver of Innovation" - ...Big Data Frankfurt meets Thinkport | "The Cloud as a Driver of Innovation" - ...
Big Data Frankfurt meets Thinkport | "The Cloud as a Driver of Innovation" - ...
 
Thinkport meets Frankfurt | "Financial Time Series Analysis using Wavelets" -...
Thinkport meets Frankfurt | "Financial Time Series Analysis using Wavelets" -...Thinkport meets Frankfurt | "Financial Time Series Analysis using Wavelets" -...
Thinkport meets Frankfurt | "Financial Time Series Analysis using Wavelets" -...
 
Big Data Helsinki v 3 | "Distributed Machine and Deep Learning at Scale with ...
Big Data Helsinki v 3 | "Distributed Machine and Deep Learning at Scale with ...Big Data Helsinki v 3 | "Distributed Machine and Deep Learning at Scale with ...
Big Data Helsinki v 3 | "Distributed Machine and Deep Learning at Scale with ...
 
Big Data Helsinki v 3 | "Federated Learning and Privacy-preserving AI" - Oguz...
Big Data Helsinki v 3 | "Federated Learning and Privacy-preserving AI" - Oguz...Big Data Helsinki v 3 | "Federated Learning and Privacy-preserving AI" - Oguz...
Big Data Helsinki v 3 | "Federated Learning and Privacy-preserving AI" - Oguz...
 

Último

Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
vu2urc
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
 

Último (20)

Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
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
 
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
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
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
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 

Gianluigi Vigano, Senior Architect and Fouad Teban, Regional Presales Manager | Big Data Platform at HPE

  • 1. Machine learning Big Data, Budapest V3.0 Gianluigi Vigano’ Fouad Teban Budapest, HU 19th of May 2016
  • 2. Use cases for Machine learning – IoT – Clickstream – Predictive maintenance – Data normalization – Demand forecasting – Cyber security – Scoring – Churn Analytics – Social graph analysis – Tickstore data cleanups 2
  • 3. Motivations of Machine Learning inside RDBMS Minimize the data movement • No need to move the data out of the RDMS to other systems to train a model • Run predictions in RDBMS, where the data is A single system for SQL analytics and machine learning A familiar interface for existing RDBMS users to do machine learning 3
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19. Machine learning with HPE Vertica Big Data, Budapest V3.0 Gianluigi Vigano’ Fouad Teban Budapest, HU 19th of May 2016
  • 20. HPE Vertica: No limits, no compromises. Supports all preferred tools Open architecture 50x-1,000x faster Blazing fast analytics Unlimited low-cost nodes Massive scalability 10x-30x more data per server Optimized data storage Private Cloud Public Cloud ApplianceSoftware Only Purpose built for Big Data - from the very first line of code Flexible deployment
  • 21. Vertica high performance advanced analytics  Real-time performance at Scale  On Premise, Cloud and On Demand  Native optimized SQL on Hadoop IDOL augmented intelligence for human information  Advanced enterprise search and rich media analytics  Analyze text, audio, image and streaming video Haven OnDemand APIs and Services  Machine Learning as a Service  Delivered on Microsoft Azure Cloud  Accessible to any developer HPE IDOL