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Powering the "As it Happens" Business


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Learn about the MapR Hadoop distribution, a data platform for the age of big data.

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Powering the "As it Happens" Business

  1. 1. © 2015 MapR Technologies 1© 2015 MapR Technologies
  2. 2. © 2015 MapR Technologies 2 MapR: Best Solution for Customer Success Premier Investors High Growth 2X Growth In Direct Customers 90% Subscription Licenses Software Margins 140% Dollar-based Net Expansion 700+ Customers 2X Growth In Annual Subscriptions ( ACV) Best Product Apache Open Source
  3. 3. © 2015 MapR Technologies 3 CIO “Must Have” Strategies Over Time Distributed Computing? Big Data? Web? Ecommerce? Cloud? Social? Mobile? Open Source?
  4. 4. © 2015 MapR Technologies 4 CIO “Must Have” Strategies Over Time Distributed Computing? Big Data? Web? Ecommerce? Cloud? Social? Mobile? Open Source? Back Office “Automation” “Cost reduction” “Retrospective” Front Office “Customer intimacy” “Revenue creation” “Just-in-time”
  5. 5. © 2015 MapR Technologies 5 Advantage From Speeding Data-to-Action Cycle The “As it Happens” Business What happened historically? What can we do to affect change? What’s happening now?
  6. 6. © 2015 MapR Technologies 6 MapR Vision Empowering the “As-it-Happens” business by speeding up the data-to-action cycle
  7. 7. © 2015 MapR Technologies 7 MapR Architected A Platform For The Age Of Big Data Apps Databases Operational App platform Storage 1980s 2000s 2010s Big data apps RDBMs SAN/NAS Monolithic UNIX Linux RDBMs Scale out Web Structured Unstructured Operational Analytics
  8. 8. © 2015 MapR Technologies 8 Alternatives Do Big OR Fast, But Not Both Big Limited reliability Limited functionality Batch (mostly) Rewrite Existing Apps Fast Expensive Special purpose Coding required for speed Limited scale Limited functionality OR
  9. 9. © 2015 MapR Technologies 9 Multiple Workloads Today Hadoop Batch Import/ Export Any Operational DBMS Customer 360° Dashboard Churn Analysis (predictive analysis) DB Operations Web Application Server Mobile Application Server Data Exploration (SQL) This is how most clients solve Big and Fast
  10. 10. © 2015 MapR Technologies 10 For the ”As-it-Happens” business: It Must Be Both Big And Fast Unlimited Scale Data diversity Evolving schemas Affordable Secure Reliable Manageable Fast ingestion Batch & streaming Polyglot RDBMS & NoSQL General purpose Affordable Big FastAND
  11. 11. © 2015 MapR Technologies 11 Integrated Real Time and Actionable Analytics Real-time Ad Targeting Product/sService Optimization and Personalization • Single cluster • Real time • High performance, low latency • Large-scale analytics • Enterprise-grade HA/DR • Unified file and table administration Customer 360° Dashboard Churn Analysis (predictive analysis) DB Operations Web Application Server Mobile Application Server Data Exploration (SQL) One Integrated System For Big & Fast
  12. 12. © 2015 MapR Technologies 12© 2015 MapR Technologies I thought all Hadoop Vendors were the same…
  13. 13. © 2015 MapR Technologies 13 Other Hadoop Distributions Have Limitations APACHE HADOOP AND OSS ECOSYSTEM Security YARN Spark Streaming Storm StreamingNoSQL & Search Juju Provisioning & coordination Savannah ML, Graph Mahout MLLib GraphX EXECUTION ENGINES DATA GOVERNANCE AND OPERATIONS Workflow & Data Governanc e Pig Cascading Spark Batch MapReduc e v1 & v2 Tez HBase Solr Hive Impala Spark SQL Drill SQL Sentry Oozie ZooKeeperSqoop Flume Data Integration & Access HttpFS Hue MapR Data Platform (Random Read/Write) Can’t scale No update in-place or handling streams Single points of failure. No data center-class reliability Batch only. Need separate systems for real time HDFS can only be a platform for Hadoop and nothing else
  14. 14. © 2015 MapR Technologies 14 MapR: The Only Platform Architected For Big, Fast, Reliable APACHE HADOOP AND OSS ECOSYSTEM Security YARN Spark Streaming Storm StreamingNoSQL & Search Juju Provisioning & coordination Savannah ML, Graph Mahout MLLib GraphX EXECUTION ENGINES DATA GOVERNANCE AND OPERATIONS Workflow & Data Governanc e Pig Cascading Spark Batch MapReduc e v1 & v2 Tez HBase Solr Hive Impala Spark SQL Drill SQL Sentry Oozie ZooKeeperSqoop Flume Data Integration & Access HttpFS Hue MapR Data Platform (Random Read/Write) MapR-FS HDFS and NFS APIs MapR-DB (High-Performance NoSQL) More efficient use of infrastructure First new database designed for operational real-time Surf any data easily Industry’s only mirroring, point- in-time consistent snapshots Trillion files Unique Unique Unique Unique Unique 2-7x faster Open source Projects ‘inherit’ MapR’s platform attributes
  15. 15. © 2015 MapR Technologies 15 Real-Time Hadoop Requirements REAL-TIME DATA REAL-TIME APPLICATIONS REAL-TIME ANALYTICS
  16. 16. © 2015 MapR Technologies 16 TechValidate: Others Say So
  17. 17. © 2015 MapR Technologies 17© 2015 MapR Technologies MapR and Teradata
  18. 18. © 2015 MapR Technologies 18 "Our customers were saying, 'Look, I have chosen Teradata as best-in-class data warehousing; I have chosen MapR as best- in-class Hadoop infrastructure. I want you guys to integrate those together,'" said Teradata Vice President of Product and Services Marketing Chris Twogood. "Amongst our customers, 90 percent of them were saying we want tighter integration.“ MapR Hadoop Gets Blessing From Data Warehouse Giant Teradata CRN, Nov 19, 2014
  19. 19. © 2015 MapR Technologies 19 Partnership Announced on November 19th, 2014 • Teradata’s UDA one-stop-shop strategy is now extended to MapR – Teradata customers get single vendor accountable for the full Hadoop ecosystem – Teradata now a strategic partner to design, implement & provide solutions with MapR • Deeper software integration between Teradata and MapR – Seamless access across the Teradata UDA – Teradata QueryGrid to support MapR – Teradata Loom fully supports MapR Distribution for Hadoop • Resell of subscriptions (license + support) for 3 core MapR products – MapR Community Edition (free version, Teradata Customer Support) – MapR Enterprise Edition (license and Teradata Customer Support) – MapR Enterprise Database Edition (license and Teradata Customer Support) • Teradata can resell Professional Services and Training curriculum – Teradata can sell MapR education and training services and professional services to Teradata customers – Through one phone call, provides single vendor accountability across the UDA MapR & Teradata Expand Partnership Partnership extends Hadoop choices by providing integration, joint product development, and unified go-to-market strategy
  20. 20. © 2015 MapR Technologies 20 • Economically Capture and Store More Data • Analytics on Low Business Value Density Data • Enterprise-grade NoSQL Database • Economically Reuse and Share Data • Analytics on High Business Value Density Data • EDW Leader Right Tool for the Right Job Teradata and MapR – Architecture Matters
  21. 21. © 2015 MapR Technologies 21 Marketing Executives Operational Systems Frontline Workers Customers Partners Engineers Data Scientists Business Analysts' Math and Stats Data Mining Business Intelligence Applications Languages Marketing APPLICATIONS USERS DISCOVERY PLATFORM INTEGRATED DATA WAREHOUSE ERP SCM CRM Images Audio and Video Machine Logs Text Web and Social SOURCES DATA PLATFORM TERADATA UNIFIED DATA ARCHITECTURE ACCESSMOVEMANAGE STREAMING & NOSQL APP’S STREAMING & NOSQL APP’S
  22. 22. © 2015 MapR Technologies 22 Capability Community Edition Enterprise Edition Enterprise Database Edition MapR Distribution including Apache Hadoop Apache Hadoop & Open Source Projects Core Hadoop, Cascading, Drill, Flume, HBase, Hive, Hue, HttpFS, Impala, Juju, Mahout, MapReduce, Oozie, Pig, Solr, the full Spark stack, Sqoop, YARN, ZooKeeper ✔ ✔ ✔ MapR Data Platform and System Management Performance ✔ ✔ ✔ Scalability ✔ ✔ ✔ Direct Access NFS™ ✔ ✔ ✔ Standards-based APIs and Tools ✔ ✔ ✔ Manageability ✔ ✔ ✔ Integrated Security ✔ ✔ ✔ Multi-tenancy ✔ ✔ ✔ Advanced Multi-tenancy ✔ ✔ Consistent Snapshots ✔ ✔ High Availability ✔ ✔ Disaster Recovery ✔ ✔ MapR-DB - integrated enterprise-grade NoSQL ✔ ✔ Support Features Community Support ✔ ✔ ✔ 24x7 Commercial Support ✔ ✔ MapR Solutions Resold by Teradata
  23. 23. © 2015 MapR Technologies 23© 2015 MapR Technologies Customers & Use Cases
  24. 24. © 2015 MapR Technologies 24 MapR Use Case Inventory HEALTHCARE & LIFE SCIENCES GOVERNMENT ADVERTISING, MEDIA & ENTERTAINMENT • Improved ad targeting, analysis, forecasting and optimization • Personalized recommendations • Superior analytics capability • Enhanced game player engagement FINANCIAL SERVICES • Fraud Detection • Customer Segmentation Analysis • Customer Sentiment Analysis • Risk Aggregation • Counterparty Risk Analytics • New Products and Services for Consumer Card Holders • Credit Risk Assessment • 360-Degree Customer Service • Cybersecurity, Intelligence • Crime Prediction and Prevention • Defense, National Security • Pharmaceutical Drug Evaluation • Scientific Research • Weather Forecasting • Fraud Detection • Emergency Communications/Response • Traffic Optimization TELECOMMANUFACTURING OIL & GAS RETAIL • Personalized Treatment Planning • Assisted Diagnosis • Fraud Detection • Monitor Patient Vital Signs • Assembly Line Quality Assurance • Preventive Maintenance • Supply Chain and Logistics • Monitoring Product Quality through Telemetry Data • Real-time Parts Flow Monitoring • Product Configuration Planning • Market Pricing and Planning • Oil Exploration and Discovery • New oil prospect identification • Seismic trace identification • Oil Production • Equipment Maintenance • Reservoir Engineering • Safety and Environment • Security • Up-Sell/Cross-Sell Recommendations • Social Media Analysis • Dynamic Pricing Across Multiple Channels • Fraud Detection • Clickstream Analysis • Loyalty Program Benefits • 360° Customer View • Operational Intelligence • Customer Churn Analysis • Fraud Detection • Clickstream Analysis • Recommendations • Product Development • Network Management/Optimization
  25. 25. © 2015 MapR Technologies 25 Cisco was able to analyze service sales opportunities in 1/10 the time, at 1/10 the cost, and generated $40 million in incremental service bookings in the first year. Cisco: 360° Customer View Cisco uses integrated customer data to increase revenues • Create shared view of customer & operations across 75,000 employees • Increase revenue opportunities with sales partners • Customer information was siloed in different divisions • Customer interactions were inconsistent and not satisfying • Missed opportunities for upselling/cross selling • Use MapR to collect customer information across touch points • Integrate billing, support, manufacturing, social media, websites, dial-in data • Generate new sales leads internally and for partners OBJECTIVES CHALLENGES SOLUTION Architecture for Sales Partner Opportunities Business Impact
  26. 26. © 2015 MapR Technologies 26 Cisco Data Platforms Reference Architecture “The entire market is starting to realize that data is everywhere and an agile ecosystem is paramount. The marketplace demands the flexibility to meet specific needs and decisions are being made based on how well the ecosystem players are integrated.” Arvind Bedi, Director IT, Cisco Systems DATABASES DOCS, CASES, CONTENT, SOCIAL MEDIA, CLICKSTEAM Data Storage and Processing ERP SFDC SAP HANA ON UCS AGILE ANALYTICS MAPR DISTRIBUTION FOR HADOOP Streaming (Spark Streaming, Storm) MapR-DB MAPR DISTRIBUTION FOR HADOOP Batch (MR, Spark, Hive, Pig, …) MapR-FS BIG DATA PLATFORM MISSION CRITICAL REPORTING DATA SECURITY, INFRASTRUCTURE CUSTOMER NETWORK, PRODUCT USAGE INTERNET OF EVERYTHING (IoE) SELF SERVICE DASHBOARD RAPID BUSINESS MODEL DATA EXPLORATION REAL TIME PREDICTIVE MISSION CRITICAL OPERATIONAL REPORTS FINANCIAL REPORTING & EXTRACT DATA ANALYSIS, TEXT ANALYTICS MACHINE LEARNING, STATISTICAL ANALYSIS MACHINE DATA INSIGHTS FINANCIALS STABLE CORE CONTROLLED CHANGE Network of Trust MapR Data Platform Data ConsumptionData Sources ALL Other Sources Data Bases (Mobile/ Browser/ Data Service) Interactive (Drill, Impala)
  27. 27. © 2015 MapR Technologies 27  Increase in Website engagement and conversion with more relevant offers  Improved customer satisfaction and reduced churn  Higher performance (35-60% faster) & reliability for customer-facing applications Improving the Customer Experience with Big Data Large brokerage increases customer acquisition rate and improves customer service • Increase conversion rate of online visitors to customers • Provide real-time response for call center agents to service customers • Inability to provide customers with right content through right channel • Lack of real-time 360 view into customers • Operational issues with prior Hadoop distribution • Easy ingestion of customer, application and clickstream data with NFS • Deeper insights to customer preferences across web, mobile, call center • Real-time contextual offers to clients using MapR-DB • Real-time streaming application for customer support with Storm on MapR OBJECTIVES CHALLENGES SOLUTION Business Impact LARGE BROKERAGE
  28. 28. © 2015 MapR Technologies 28 MAPR DISTRIBUTION FOR HADOOP NFS, Sqoop, Flume MapR-DB Hive & Datameer Ingest, Transform, Enrichment (Batch Processing) Interactive analytics Operational Drill MapR-FS Streaming MapR Data Platform MapR-FS MapR-DB Storm Architecture and Use Cases Data Movement Data Access Relevant customer offers & experience CUSTOMIZED FINANCIAL PRODUCT CONTEXTUAL CUSTOMER SUPPORT Real-time call center response CUSTOMER 360 & WEB Web Clickstream (Omniture) Application Logs (Splunk) Customer Data (Teradata) Data Sources Customer 360 database DISTRIBUTION FOR HADOOP 160 customer attributes Call Center Records
  29. 29. © 2015 MapR Technologies 29 For More Details Visit
  30. 30. © 2015 MapR Technologies 30 Freeon-demand Hadoop training leading to certification Start becoming an expert now 50MIn Free Training
  31. 31. © 2015 MapR Technologies 31 Q&A @mapr maprtech Engage with us! MapR maprtech mapr-technologies