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Terracotta Hadoop & In-Memory Webcast
 

Terracotta Hadoop & In-Memory Webcast

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Hadoop is sparking a Big Data analytics revolution. But all the Hadoop insights in the world are worth nothing unless they lead to new, profitable action. To translate Hadoop insights into action in ...

Hadoop is sparking a Big Data analytics revolution. But all the Hadoop insights in the world are worth nothing unless they lead to new, profitable action. To translate Hadoop insights into action in real time, more and more enterprises are combining Hadoop with the power of in-memory computing.
Join us as we outline the tremendous benefits of merging Hadoop with in-memory data management, the challenges of doing so, and tips for getting started.

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    Terracotta Hadoop & In-Memory Webcast Terracotta Hadoop & In-Memory Webcast Presentation Transcript

    • © 2013 Terracotta Inc. | Internal Use OnlyIn-Memory &Hadoop:Real-timeBig Data Intelligence
    • © 2013 Terracotta Inc. 2Your speakerManish DevganDirector of ProductManagementTerracotta
    • © 2013 Terracotta Inc. 3What we’ll cover in this webcast• What’s Hadoop? (quick intro)• Hadoop’s weaknesses• Emerging best practices for combiningHadoop and in-memory data management• Real-time intelligence example• Getting started with in-memory and Hadoop• Q & A
    • © 2013 Terracotta Inc. 44© 2013 Terracotta Inc. | Internal Use OnlyWhat is Hadoop?
    • © 2013 Terracotta Inc. 5What is ?• Hadoop is open-source software data management frameworkused to draw insights from dataComponents BenefitsHDFS*: Scalable &distributed Storage• Data distributed across clusternodes• Name node keeps track of locationMapReduce: ParallelProcessing of data• Splits a task for processing basedon data locality and thenassembles results• Comprises of Map() procedure forfiltering & sorting and Reduce()procedure for summarizingScalable• Efficiently store and process largedata setsReliable• Get redundant storage, with failoveracross clusterRich & Flexible• Complimentary set of tools &frameworks• Store data in any formatEconomical• Deploy on commodity hardware*Hadoop Distributed File System
    • © 2013 Terracotta Inc. 6What is ?• With Hadoop, you can ask interesting questions about your dataand get answers economicallyQuestions Hadoop can help answerHow can I target promotions to my customers for bettersales?How risky are each of my customers?Which advertisement should I show to optimize return?How relevant is a result for a given search?When will my machinery likely have a malfunction?
    • © 2013 Terracotta Inc. 77© 2013 Terracotta Inc. | Internal Use OnlyHadoop’s Weaknesses
    • © 2013 Terracotta Inc. 8Hadoop’s Weaknesses• No support for real-time insights• No support to facilitate interactive and exploratory data analysis• Challenging framework for computation beyond Map Reduce• Lacks tools for business analysts
    • © 2013 Terracotta Inc. 99© 2013 Terracotta Inc. | Internal Use OnlyEmerging best practicesfor combining Hadoop andin-memory data management
    • © 2013 Terracotta Inc. 10Combining Hadoop and In-memory Data Management- Businesses are looking for ways to mine real-time insights toprovide competitive advantages- Increased adoption of transactional system data for analytics isblurring the line between OLTP and OLAP- New frameworks and products are bringing in-memorytechnologies to the Hadoop ecosystem
    • © 2013 Terracotta Inc. 11Real-time Data Integration with HadoopWebAppsMobileAppsDashboards& MashupsIn-memory Data Management PlatformReal-time Data AppsTransactionalAppsOperationalIntelligenceLog Data POS Data Social Media SensorsData SourcesEventsImages/VideosData FeedsReal-timedataReal-timeInsights
    • © 2013 Terracotta Inc. 1212© 2013 Terracotta Inc. | Internal Use OnlyReal-time intelligence example
    • © 2013 Terracotta Inc. 13BigMemory & Hadoop in financial servicesBefore: Custom ETL connector pushing batch dataHadoop ClusterBigMemoryStoreShort TermTransactionDataLong TermTransactionDataRules &TriggersTaggedAccountsCreditReferenceDataHDFS to BigMemoryProcessingHadoop M/R
    • © 2013 Terracotta Inc. 14BigMemory & Hadoop in financial servicesToday: Streaming Data insightsHadoop ClusterInsights Hadoop M/RBigMemory-HadoopConnectorBigMemoryStoreShort TermTransactionDataLong TermTransactionDataRules &TriggersTaggedAccountsCreditReferenceData
    • © 2013 Terracotta Inc. 1515© 2013 Terracotta Inc. | Internal Use OnlyGetting started within-memory and Hadoop
    • © 2013 Terracotta Inc. 16How to get started with In-memory and Hadoop?• If you already have a Hadoop project, look for use cases whereyou want real-time access to insights• Start with a small-to-medium sized (20-40 nodes) cluster with awell-defined use case requiring fast access to data• Consider exploratory use cases where you’re doing iterativeanalysis on a data set to get answers faster
    • © 2013 Terracotta Inc. 17In-Memory & HadoopQuestionsPlease type yours in the “Questions” panel or in the chat window.
    • © 2013 Terracotta Inc. 18Connect with Terracotta• Download “BigMemory & Hadoop” white paper− Visit: www.terracotta.org (Resources > White Papers)• Download “BigMemory-Hadoop Connector”− Visit: www.terracotta.org/downloads/hadoop-connector• Contact Manish Devgan− Email: mdevgan@terracottatech.com• Follow us on Twitter− @big_memory• Stay Tuned