Introduction to Hadoop - Edureka

Introduction to Hadoop - Edureka Introduction to Hadoop Back Home Categories Online Courses Mock Interviews Webinars NEW Community Write for Us Categories Artificial Intelligence AI vs Machine Learning vs Deep LearningMachine Learning AlgorithmsArtificial Intelligence TutorialWhat is Deep LearningDeep Learning TutorialInstall TensorFlowDeep Learning with PythonBackpropagationTensorFlow TutorialConvolutional Neural Network TutorialVIEW ALL BI and Visualization What is TableauTableau TutorialTableau Interview QuestionsWhat is InformaticaInformatica Interview QuestionsPower BI TutorialPower BI Interview QuestionsOLTP vs OLAPQlikView TutorialAdvanced Excel Formulas TutorialVIEW ALL Big Data What is HadoopHadoop ArchitectureHadoop TutorialHadoop Interview QuestionsHadoop EcosystemData Science vs Big Data vs Data AnalyticsWhat is Big DataMapReduce TutorialPig TutorialSpark TutorialSpark Interview QuestionsBig Data TutorialHive TutorialVIEW ALL Blockchain Blockchain TutorialWhat is BlockchainHyperledger FabricWhat Is EthereumEthereum TutorialB lockchain ApplicationsSolidity TutorialBlockchain ProgrammingHow Blockchain WorksVIEW ALL Cloud Computing What is AWSAWS TutorialAWS CertificationAzure Interview QuestionsAzure TutorialWhat Is Cloud ComputingWhat Is SalesforceIoT TutorialSalesforce TutorialSalesforce Interview QuestionsVIEW ALL Cyber Security Cloud SecurityWhat is CryptographyNmap TutorialSQL Injection AttacksHow To Install Kali LinuxHow to become an Ethical Hacker?Footprinting in Ethical HackingNetwork Scanning for Ethical HackingARP SpoofingApplication SecurityVIEW ALL Data Science Python Pandas TutorialWhat is Machine LearningMachine Learning TutorialMachine Learning ProjectsMachine Learning Interview QuestionsWhat Is Data ScienceSAS TutorialR TutorialData Science ProjectsHow to become a data scientistData Science Interview QuestionsData Scientist SalaryVIEW ALL Data Warehousing and ETL What is Data WarehouseDimension Table in Data WarehousingData Warehousing Interview QuestionsData warehouse architectureTalend T utorialTalend ETL ToolTalend Interview QuestionsFact Table and its TypesInformatica TransformationsInformatica TutorialVIEW ALL Databases What is MySQLMySQL Data TypesSQL JoinsSQL Data TypesWhat is MongoDBMongoDB Interview QuestionsMySQL TutorialSQL Interview QuestionsSQL CommandsMySQL Interview QuestionsVIEW ALL DevOps What is DevOpsDevOps vs AgileDevOps ToolsDevOps TutorialHow To Become A DevOps EngineerDevOps Interview QuestionsWhat Is DockerDocker TutorialDocker Interview QuestionsWhat Is ChefWhat Is KubernetesKubernetes TutorialVIEW ALL Front End Web Development What is JavaScript â€" All You Need To Know About JavaScriptJavaScript TutorialJavaScript Interview QuestionsJavaScript FrameworksAngular TutorialAngular Interview QuestionsWhat is REST API?React TutorialReact vs AngularjQuery TutorialNode TutorialReact Interview QuestionsVIEW ALL Mobile Development Android TutorialAndroid Interview QuestionsAndroid ArchitectureAndroid SQLite DatabaseProgramming Introduction to Hadoop, which was conducted on 8th August14.Introduction to HadoopBig Data is a term for collection of data sets so large and complex that it becomes difficult to process using hands-on database management tools or traditional data processing applications.Big Data has now become a popular term to describe the explosion of data and Hadoop has become synonymous with Big Data.Doug Cutting, created ApacheHadoop for this very reason. Hadoop has now become the de facto standard for storing, processing and analyzing hundreds of terabytes, and even petabytes of data.Hadoop allows distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that store and process data.The above video covers the following topics in detail:What is Big DataTraditional Warehouse Vs HadoopWhy Should you Learn Hadoop and Related TechnologiesJobs and Trends in Big DataHadoop Architecture and EcosystemPresentation:Why Should you Learn Hadoop Related Technologies?Unstructured Data is Exploding Digital universe has grown by 62% last year, to 800k petabytes and will grow further to 1.2 zettabytes by the end of this year.Big Data Challenges Increasing volume of data from various sources with different data types are imposing huge challenges.Big Data Customer Scenarios:Here are some use cases of Big Data in Retail, Banking and Financial sectors:Banking and Financial Services:Modeling True RiskThreat AnalysisFraud DetectionTrade SurveillanceCredit Scoring and AnalysisRetail:Point of Sales Transaction AnalysisCustomer Churn AnalysisSentiment AnalysisCase Study:This video includes a case study where the usage of Hadoop by Sears has been discussed. Sears was previously using traditional systems such as Oracle Exadata, Teradata and SAS to store and process the customer activity and sales data. On adapting Hadoop, Sears gained valuable advantages like :Insights in to data provided valuable business advantageKey early indicators that means fortune to businessPrecise analy sis with more dataLimitations of Existing Data Analytics Architecture and How Hadoop Overcomes it:The video has a step by step explanation of the flow of data and limitation faced by it in existing data analytics architecture and how Hadoop over comes it. Hadoop provides a solution where a combined storage computer layer is utilized. As a result, Sears moved to 300 node Hadoop cluster to keep 100% of its data for processing rather than the meager 10% that was available in the existing non-Hadoop solutions.Why Move to Hadoop?The following reasons make it pretty clear as to why one must move to Hadoop.Allows distributed processing of large sets of data across clusters of computers using simple programming model.Has become the de facto standard for storing, processing and analyzing hundreds of terabytes and petabytes of data.Cheaper to use, in comparison with other traditional proprietary technologies.Handles all types of data from disparate systems.Hadoop Growth and Job Opportunities :Weve heard its a fad, heard its hyped and heard its fleeting, yet its clear that data professionals are in demand and well paid. Tech professionals who analyse large data streams and strategically impact the overall business goals of a firm have an opportunity to write their own ticket. said Alice Hill, Managing Director of Dice.com.As per the 2012-13 Salary Survey by Dice, a leading career site for technology and engineering professionals: Big Data jobs are having positive, disproportionate impact on salaries.Professionals with Hadoop, NoSQL and MongoD skills can earn more than $100,000Gartner Says Big Data will be creating 4.4 Million IT Jobs Globally to support Big Data, By 2015. Click here to know more about the demand for Hadoop.Hadoop Ecosystem Architecture:Hadoop comprises of two main components:HDFS Hadoop Distributed File System For StorageHighly fault-tolerantHigh throughput access to application dataSuitable for applications that have large data setNatively redundantM apReduce For ProcessingSoftware framework for easily writing applications which process vast amounts of data (multi-terabyte data-sets) in-parallel on large clusters (thousands of nodes) in a reliable, fault-tolerant mannerSplits a task across processorsGot a question for us? Mention it in the comments section and we will get back to you.Related Posts:Hadoop for Java ProfessionalsIs Big Data the Right Move for You?5 Reasons to Learn HadoopBig Data and Hadoop TrainingRecommended videos for you New-Age Search through Apache Solr Watch Now Hadoop Cluster With High Availability Watch Now Power of Python With BigData Watch Now Apache Spark Redefining Big Data Processing Watch Now Apache Spark For Faster Batch Processing Watch Now What is Apache Storm all about? Watch Now Streaming With Apache Spark and Scala Watch Now 5 Things One Must Know About Spark Watch Now Is Hadoop A Necessity For Data Science? Watch Now Top Hadoop Interview Questions and Answers Ace Your Interview Watch Now Big Data Tutorial Get Started With Big Data And Hadoop Watch Now Apache Spark Will Replace Hadoop ! 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