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Zementis hortonworks-webinar-2014-09

see the recording: http://youtu.be/qdhF1sfef10 Ofer Medelvitch, Director of Data Science of Hortonworks and Michael Zeller, Founder and CEO of Zementis present key learnings as to what drives successful implementations of big data analytics projects. Their knowledge comes from working with dozens of companies from small cloud-based start-ups to some of the largest companies in the world.

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Webinar will begin shortly… 
! 
Hadoop’s Advantages for 
Machine Learning and 
Predictive Analytics 
!!!!!! 
Presented by Hortonworks & Zementis 
! 
September 10, 2014 
Copyright 2014 Zementis, Inc. All rights reserved. 2
Moderator Presenters 
! 
! 
Copyright 2014 Zementis, Inc. All rights reserved. 
4 
Hadoop’s Advantages for 
Machine Learning and Predictive Analytics 
Mark Rabkin 
Director Business Development 
Zementis 
Ofer Mendelevitch 
Director of Data Science 
Hortonworks 
Michael Zeller 
CEO 
Zementis
The Speakers 
Michael Zeller 
CEO & Founder 
Zementis 
Ofer Mendelevitch 
Director of Data Science 
Hortonworks 
Ofer Mendelevitch is Director of data sciences 
at Hortonworks, where he is responsible for 
professional services involving data science 
with Hadoop, including use-cases like 
recommender systems, prediction, 
classification and search. Prior to joining 
Hortonworks, Ofer has held a number of 
positions from Entrepreneur in Residence at 
XSeed Capital, VP of Engineering at Nor1 and 
Director of engineering at Yahoo! where he led 
multiple engineering and data science teams. 
Michael Zeller is the CEO and Co-Founder of 
Zementis. His vision is to help companies 
deepen and accelerate insights from big data 
through the power of predictive analytics. Michael 
also serves on the Board of Directors of Software 
San Diego and as Secretary/Treasurer on the 
Executive Committee of ACM SIGKDD, which is 
the premier international organization for data 
mining researchers and practitioners from 
academia, industry, and government. 
Copyright 2014 Zementis, Inc. All rights reserved. 5
Hortonworks: We Do Hadoop. 
Our mission is to power your 
Modern Data Architecture by 
delivering Enterprise Apache 
Hadoop 
Reseller 
Partners: 
Copyright 2014 Zementis, Inc. All rights reserved. 
Zementis provides software for 
operational deployment of 
predictive analytics 
Products & Capabilities: 
• Vendor-neutral architecture for 
- Data mining tools 
- Analytics and data warehouse 
platforms 
• Supports PMML industry standard and 
wide range of predictive modeling 
techniques 
• Rapidly deploys and executes predictive 
models 
• Accelerates business insight 
6 
Hortonworks & Zementis 
Our Commitment: 
• Open Leadership 
Drive innovation in the open exclusively 
via the Apache community-driven open 
source process 
• Enterprise Rigor 
Engineer, test and certify Apache Hadoop 
with the enterprise in mind 
• Ecosystem Endorsement 
Focus on deep integration with existing 
data center technologies and skills
A data architecture under pressure from new data 
DATA**SYSTEM* APPLICATIONS* 
Business** 
Analy4cs* 
RDBMS* EDW* MPP* 
REPOSITORIES* 
SOURCES* 
Exis4ng*Sources** 
Custom* 
Applica4ons* 
(CRM,*ERP,*Clickstream,*Logs)* 
Page 1 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
Packaged* 
Applica4ons* 
2.8*ZB*in*2012* 
85%*from*New*Data*Types* 
15x*Machine*Data*by*2020* 
40*ZB*by*2020* 
Source: IDC 
OLTP,&ERP,&CRM&Systems& 
Unstructured&documents,&emails& 
Server&logs& 
Clickstream& 
Sen>ment,&Web&Data& 
Sensor.&Machine&Data& 
GeoEloca>on&
Hadoop within an emerging Modern Data Architecture 
Page 2 © Hortonworks Inc. 2011 – 2014. All Rights Reserved 
DEV*&*DATA*TOOLS* 
Build & 
Test 
OPERATIONS*TOOLS* 
Provision, 
Manage & 
Monitor 
DATA**SYSTEM* 
REPOSITORIES* 
SOURCES* 
RDBMS* EDW* MPP* 
OLTP,&ERP,& 
CRM&Systems& 
Documents,&& 
Emails& 
Web&Logs,& 
Click&Streams& 
Social& 
Networks& 
Machine& 
Generated& 
Sensor& 
Data& 
Geoloca>on& 
Data& 
Governance 
& Integration 
Security 
Operations 
Data Access 
Data Management 
APPLICATIONS* 
Business** 
Analy4cs* 
Custom* 
Applica4ons* 
Packaged* 
Applica4ons* 
Data Lake 
An architectural shift in the 
data center that uses Hadoop 
to deliver deeper insight across 
a large, broad, diverse set of 
data at efficient scale

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Zementis hortonworks-webinar-2014-09

  • 1. Webinar will begin shortly… ! Hadoop’s Advantages for Machine Learning and Predictive Analytics !!!!!! Presented by Hortonworks & Zementis ! September 10, 2014 Copyright 2014 Zementis, Inc. All rights reserved. 2
  • 2. Moderator Presenters ! ! Copyright 2014 Zementis, Inc. All rights reserved. 4 Hadoop’s Advantages for Machine Learning and Predictive Analytics Mark Rabkin Director Business Development Zementis Ofer Mendelevitch Director of Data Science Hortonworks Michael Zeller CEO Zementis
  • 3. The Speakers Michael Zeller CEO & Founder Zementis Ofer Mendelevitch Director of Data Science Hortonworks Ofer Mendelevitch is Director of data sciences at Hortonworks, where he is responsible for professional services involving data science with Hadoop, including use-cases like recommender systems, prediction, classification and search. Prior to joining Hortonworks, Ofer has held a number of positions from Entrepreneur in Residence at XSeed Capital, VP of Engineering at Nor1 and Director of engineering at Yahoo! where he led multiple engineering and data science teams. Michael Zeller is the CEO and Co-Founder of Zementis. His vision is to help companies deepen and accelerate insights from big data through the power of predictive analytics. Michael also serves on the Board of Directors of Software San Diego and as Secretary/Treasurer on the Executive Committee of ACM SIGKDD, which is the premier international organization for data mining researchers and practitioners from academia, industry, and government. Copyright 2014 Zementis, Inc. All rights reserved. 5
  • 4. Hortonworks: We Do Hadoop. Our mission is to power your Modern Data Architecture by delivering Enterprise Apache Hadoop Reseller Partners: Copyright 2014 Zementis, Inc. All rights reserved. Zementis provides software for operational deployment of predictive analytics Products & Capabilities: • Vendor-neutral architecture for - Data mining tools - Analytics and data warehouse platforms • Supports PMML industry standard and wide range of predictive modeling techniques • Rapidly deploys and executes predictive models • Accelerates business insight 6 Hortonworks & Zementis Our Commitment: • Open Leadership Drive innovation in the open exclusively via the Apache community-driven open source process • Enterprise Rigor Engineer, test and certify Apache Hadoop with the enterprise in mind • Ecosystem Endorsement Focus on deep integration with existing data center technologies and skills
  • 5. A data architecture under pressure from new data DATA**SYSTEM* APPLICATIONS* Business** Analy4cs* RDBMS* EDW* MPP* REPOSITORIES* SOURCES* Exis4ng*Sources** Custom* Applica4ons* (CRM,*ERP,*Clickstream,*Logs)* Page 1 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Packaged* Applica4ons* 2.8*ZB*in*2012* 85%*from*New*Data*Types* 15x*Machine*Data*by*2020* 40*ZB*by*2020* Source: IDC OLTP,&ERP,&CRM&Systems& Unstructured&documents,&emails& Server&logs& Clickstream& Sen>ment,&Web&Data& Sensor.&Machine&Data& GeoEloca>on&
  • 6. Hadoop within an emerging Modern Data Architecture Page 2 © Hortonworks Inc. 2011 – 2014. All Rights Reserved DEV*&*DATA*TOOLS* Build & Test OPERATIONS*TOOLS* Provision, Manage & Monitor DATA**SYSTEM* REPOSITORIES* SOURCES* RDBMS* EDW* MPP* OLTP,&ERP,& CRM&Systems& Documents,&& Emails& Web&Logs,& Click&Streams& Social& Networks& Machine& Generated& Sensor& Data& Geoloca>on& Data& Governance & Integration Security Operations Data Access Data Management APPLICATIONS* Business** Analy4cs* Custom* Applica4ons* Packaged* Applica4ons* Data Lake An architectural shift in the data center that uses Hadoop to deliver deeper insight across a large, broad, diverse set of data at efficient scale
  • 7. Hadoop unlocks a new approach: Iterative Analytics Page 3 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Hadoop* Mul>ple&Query&Engines& Itera>ve&Process:&Explore,&Transform,&Analyze& SQL* Single&Query&Engine& Repeatable&Linear&Process& ✚ Determine* list*of* ques4ons* Design* solu4ons* Collect* structured* data* Ask* ques4ons* from*list* Detect* addi4onal* ques4ons* Batch* Interac4ve* Real4me* Streaming* Current Reality Apply schema on write Dependent on IT Augment w/ Hadoop Apply schema on read Support range of access patterns to data stored in HDFS: polymorphic access
  • 8. A (partial) map of machine learning “tasks” Discovery Clustering Detect natural groupings Outlier detection Detect anomalies Association rule mining Co-occurrence patterns Page 4 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Prediction Classification Predict a category Regression Predict a value Recommendation Predict a preference
  • 9. Typical iterative flow in machine learning modeling Clean Data Page 5 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Page 5 Visualize, Explore Hypothesize; Model Measure/ Evaluate Acquire Data Deploy & Monitor
  • 10. Why Apache Hadoop for Data Science? • Hadoop’s schema-on-read reduces cycle time • Hadoop is ideal for pre-processing of raw data – Structured & unstructured • Larger datasets enable better models • Large-scale parallel scoring Page 6 © Hortonworks Inc. 2011 – 2014. All Rights Reserved
  • 11. Hadoop’s schema-on-read accelerates innovation I&need&new& data& “Schema change” project Let&me&see…&is& it&any&good?& Page 7 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Finally,&we& start& collec>ng& Let&me&see…&is& it&any&good?& Start 6 months 9 months Let’s&just&put&it&in&a& folder&on&HDFS& 3 months My&model&is& awesome!&
  • 12. Hadoop is ideal for large scale pre-processing Page 8 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Sample& Transform& Aggregate& Normalize& Join& OCR& Raw&Data& Feature& Matrix& NLP&
  • 13. Hadoop enables modeling with larger datasets Larger datasets ! better outcomes Page 9 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Banko & Brill, 2001 • More examples • More features
  • 14. Hadoop enables large-scale parallelized “scoring” Training set Page 10 © Hortonworks Inc. 2011 – 2014. All Rights Reserved Learning Model PMML Native Test set Scoring Output Embarrassingly Parallel Using Hadoop as grid compute infrastructure
  • 15. What is PMML? • Mature standard developed by the DMG (Data Mining Group) to avoid proprietary issues and incompatibilities and to deploy models ! • XML-based language used to define statistical and data mining models and to share these between compliant applications ! • Supported by most leading data mining tools, commercial and open-source ! • Data handling and transformations (pre-and post-processing) are a core component of the PMML standard ! • Allows for the clear separation of tasks: Model development vs. model deployment ! • Eliminates the need for custom code and proprietary model deployment solutions Copyright 2014 Zementis, Inc. All rights reserved. 8 Predictive Model Markup Language (PMML) industry standard reduces the complexity of operationalizing models
  • 16. Predictive Analytics Workflow PMML in action, covering a complete workflow from raw data input to decision output PMML File! Data Pre- Processing! Predictive! Model! Model ! Outputs! Derived ! Model Inputs! Data Post- Processing! Raw Inputs! Prediction! Input! Validation Outliers, ! Model! Signature Missing Values,! Invalid Values Normalize,! Discretize, Bin,! Map, etc. Scaling,! Business Decisions,! Thresholds, etc. Data and! operational types Copyright 2014 Zementis, Inc. All rights reserved. Confidential 9
  • 17. Path to Business Value Big Data Applications Cloud Log Files RSS Feeds Other Sources Predictive Models Machine Learning Techniques Data Mining Tools Copyright 2014 Zementis, Inc. All rights reserved. Business Insights Business Value Decisions & Actions • Accelerated time-to-market • More precise targeting • Real-time responsiveness • Enhanced operational agility • Competitive advantage • Higher revenue growth rates • Greater profitability • More relevant • More accurate • More comprehensive • More nuanced • Faster • Lower risk • Greater positive impact Predictive Analytics Databases 10 Predictive analytics helps organizations unlock the value of their big data …
  • 18. Predictive model deployment becomes a rework cycle • Extensive manual coding • Cross-checking • Fixing coding errors Copyright 2014 Zementis, Inc. All rights reserved. • Delayed insight • Less accurate decisions • Missed opportunities • Loss of value Traditional Deployment Cycle Develop Operationalize Utilize Data Scientist IT Engineer Business Decisions Business Professional 11 … but model deployment challenges can often erode much of the value that predictive analytics can deliver
  • 19. Deployment with Zementis & PMML Time-to-insight Within 2 days * Copyright 2014 Zementis, Inc. All rights reserved. ~ 6 months Without Zementis With Zementis Economic Value Model Deployment Cycle Time * And sometimes even within a few hours! • Accelerated deployment timeline • Reduced model deployment cycle time • Reduced model deployment expense • Increased model throughput • Enhanced accuracy • Minimal rework, if any Rapid insight Rapid time-to-value from predictive analytics = 12 Enter Zementis, whose solutions accelerate time-to-insight for predictive analytics
  • 20. Universal PMML Plug-in (UPPI) Model Deployment! Integration/Execution Data Mining Tools Commercial Vendors (e.g. IBM SPSS, SAS)! Open Source Tools (R, KNIME, ...) Predictive Algorithms Decision Trees! Neural Networks! Support Vector Machines! Linear and Logistic Regression! Naive Bayes Classifiers! General and Generalized Linear Models! Cox Regression! Rule Set Models! Clustering! Scorecards! Association Rules! Multiple Models (Segmentation, Chaining, Composition and Ensemble, including Random Forest Models) Zementis UPPI! for Hive/Hadoop Simple Deployment & Execution! Upload PMML file(s) in Hive! PMML turns into HiveQL functions! Seamlessly score data on Hadoop PMML Copyright 2014 Zementis, Inc. All rights reserved. Confidential 13
  • 21. Hive 0.13 Now faster than ever, up to 100x performance improvements and more to come… Copyright 2014 Zementis, Inc. All rights reserved. Confidential 14
  • 22. 100 50 Speeding Up Performance with Tez & ORC ! 100 21% 75 50 25 Copyright 2014 Zementis, Inc. All rights reserved. Confidential 15 UPPI for Hive 0.13 Performance Scaling by Hadoop Cluster Size Time 0 10 Nodes 20 Nodes Time 0 29% Performance executing a complex PMML model as UDF (User-Defined Function) using Hive 0.13 29% performance improvement when executing the same model and data by enabling Tez & ORC Hive! Tez Tez & ORC 0.13
  • 23. DEMO! Zementis Universal PMML Plug-in (UPPI) demo on Hortonworks Sandbox Zementis! UPPI for Hive 1. PMML Sample Models > Hive UDFs 2. Run Customer Churn Example Copyright 2014 Zementis, Inc. All rights reserved. 16
  • 24. Broad Applicability Fraud & Risk Scoring • Financial institutions • Scoring bureaus • Fraud detection • Advanced decision management Copyright 2014 Zementis, Inc. All rights reserved. Marketing & Sales • Up- /cross-sell and next-best- offer • Marketing campaign optimization • Real-time recommendations Sensor & Device Data Processing • Rotating equipment • Energy • Biometrics • IP network security 17 Hortonworks and Zementis products accelerate predictive model insights for multiple industries and business use cases
  • 25. Thank You! Questions? Copyright 2014 Zementis, Inc. All rights reserved. 18