Hadoop Stories Tim Marston Director, Regional Alliances EMEA Page 1 @timmarston
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Plans for Hadoop Adoption (Gartner, May 2015) Start within 1 year 11% Start within 2 years 7% Already doing 27% No Plans 55% Page 3
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Plans for Hadoop Adoption (Gartner, May 2015) Start within 1 year 11% Start within 2 years 7% Already doing 27% No Plans 55% Page 5
Hortonworks: Hadoop for the Enterprise ONLY Apache 100 open source TM % Hadoop data platform Founded in 2011 1 ST HADOOP distribution to go public IPO Fall 2014 (NASDAQ: HDP) 700+ subscription customers employees 800+ across 1350+ 17 technology partners countries Page 6
The Modern Data Architecture ANALYTICS Data Applications Marts Business Analytics Visualization & Dashboards Applications can be given access to all data through a single platform Batch MP P Batch EDW Batch Interactive Real-Time Partner ISV YARN: Data Operating System HDFS (Hadoop Distributed File System) Simpler governance, security and operations SOURCES ERP CRM SCM Existing Systems Clickstream Web & Social Geolocation Sensor & Machine Server Logs Unstructured Able to handle all sizes and types of applications and datasets Page 7
The Hadoop Journey Page 8
IT executives are delivering substantial reductions in operating costs by modernizing their data architectures with Open Enterprise Hadoop. These cost saving innovations include active archive of cold data, offloading ETL processes and enriching existing data. OPEX Reduction Device Data Ingest Data as a Service Historical Records Fraud Prevention Mainframe Offloads Rapid Reporting Digital Protection Public Data Capture Page 9
Payment Tracking Due Diligence Sentiment Analysis Social Mapping Customer Support Optimize Inventories Next Product Recs Store Design Call Analysis Machine Data Product Design M & A Ad Placement Basket Analysis Segments Proactive Repair Disaster Mitigation Investment Planning Factory Yields Defect Detection Cross- Sell Supply Chain Customer Retention Vendor Scorecards Inventory Predictions Risk Modeling Ad Placement Business executives are driving transformational outcomes with next-generation applications that empower new uses of Big Data including: data discovery, a single view of the customer and predictive analytics. Page 10
The Vision: Enabling the Data Lake SCALE Journey to the Data Lake with Hadoop Systems of Insight DATA LAKE Goal: Centralized Architecture Data-driven Business Data Lake Definition Centralized Architecture Multiple applications on a shared data set with consistent levels of service Any App, Any Data Multiple applications accessing all data affording new insights and opportunities. Unlocks Systems of Insight Advanced algorithms and applications used to derive new value and optimize existing value. Drivers: 1. Cost Optimization 2. Advanced Analytic Apps Page 11 SCOPE
Data Archive for legal cases Project cash positive after 12 months, with order of magnitude Opex savings once implemented. Page 12 Source: http://www.slideshare.net/hadoop_summit/making-the-case-for-hadoop-in-a-large-enterprisebritish-airways
Self-learning cars...if British manufacturing is to survive it needs to be competitive. And it cannot be competitive without data. Page 13 Source: https://diginomica.com/2015/09/11/using-hadoop-inside-jaguar-land-rover-zurich-insurance-and-the-home-office/
Modern Data Architecture The aim is to use Hadoop, a mix of internal and external data, to take Zurich Insurance to the next level of maturity in terms of using data to drive business decisions. Page 14 Source: https://diginomica.com/2015/09/11/using-hadoop-inside-jaguar-land-rover-zurich-insurance-and-the-home-office/
Hadoop at Scale 1300 Hadoop nodes, 42PB stored 20TB ingested via Kafka per day 200TB generated by Hadoop per day Page 15 Source: http://cdn.oreillystatic.com/en/assets/1/event/118/the%20evolution%20of%20hadoop%20at%20spotify-%20through%20failures%20and%20pain%20presentati
The Future? Page 16
The 100% open source Hadoop distribution Page 17
Hortonworks DataFlow Hortonworks DataFlow powered by Apache NiFi Perishable Insights Store Data and Metadata Enrich Context Internet of Anything Hortonworks Data Platform powered by Apache Hadoop Hortonworks Data Platform powered by Apache Hadoop Historical Insights Page 18
Appendix Page 19
Hortonworks Influences the Apache Community We Employ the Committers --one third of all committers to the Apache Hadoop project, and a majority in other important projects Our Committers Innovate and expand Open Enterprise Hadoop We Influence the Hadoop Roadmap by communicating important requirements to the community through our leaders APACHE HADOOP COMMITTERS Page 20
OPEN COMMUNITY THE INNOVATION ADVANTAGE PROPRIETARY HADOOP TIME INNOVATION Hortonworks Data Platform Is Genuinely Open Eliminates Risk of vendor lock-in by delivering 100% Apache open source technology Maximizes Community Innovation with hundreds of developers across hundreds of companies Integrates Seamlessly through committed co-engineering partnerships with other leading technologies MAXIMUM COMMUNITY INNOVATION Page 21
Hortonworks Delivers Proactive Support Integrated Customer Portal Knowledge Base On-Demand Training Hortonworks SmartSense Customer Environment Any cloud Hybrid Environment Multi-tenant Hortonworks SmartSense with machine learning and predictive analytics on your cluster Integrated Customer Portal with knowledge base and on-demand training Page 22
The Open Data Platform April 14 HDP Open Platform with Apache Hadoop Pivotal HD Common ODP Core Apache Hadoop and Apache Ambari Page 23
The Data Governance Initiative Hadoop must snap in to the existing frameworks and openly exchange metadata. Hadoop must address governance within its own stack of technologies Page 24
Cautionary Statement Regarding Forward-Looking Statements This presentation contains forward-looking statements involving risks and uncertainties. Such forward-looking statements in this presentation generally relate to future events, our ability to increase the number of support subscription customers, the growth in usage of the Hadoop framework, our ability to innovate and develop the various open source projects that will enhance the capabilities of the Hortonworks Data Platform, anticipated customer benefits and general business outlook. In some cases, you can identify forward-looking statements because they contain words such as may, will, should, expects, plans, anticipates, could, intends, target, projects, contemplates, believes, estimates, predicts, potential or continue or similar terms or expressions that concern our expectations, strategy, plans or intentions. You should not rely upon forward-looking statements as predictions of future events. We have based the forward-looking statements contained in this presentation primarily on our current expectations and projections about future events and trends that we believe may affect our business, financial condition and prospects. We cannot assure you that the results, events and circumstances reflected in the forward-looking statements will be achieved or occur, and actual results, events, or circumstances could differ materially from those described in the forward-looking statements. The forward-looking statements made in this prospectus relate only to events as of the date on which the statements are made and we undertake no obligation to update any of the information in this presentation. Trademarks Page 25 Hortonworks is a trademark of Hortonworks, Inc. in the United States and other