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Cetas Analytics as a Service for Predictive Analytics

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Cetas Analytics as a Service for Predictive Analytics

  1. 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. 2. INSTANT INTELLIGENCE Transform IT + Transform Business + Transform Yourself Leverage Cetas to Transform Real-Time and Predictive Analytics 2
  3. 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. 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. 5. Data Growth in the Enterprise INSTANT INTELLIGENCE 5
  6. 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. 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. 8. Trend: Big Data Analytics – Driven by Real-World Benefit INSTANT INTELLIGENCE 8
  9. 9. Big Data Use Cases INSTANT INTELLIGENCE 9
  10. 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. 11. Big Data Technology Stack INSTANT INTELLIGENCE 11
  12. 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. 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. 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. 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. 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. 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. 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. 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

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