AWS Big Data Certification Training - Simplilearn

AWS Big DataCertification Training

Table of Contents:Program OverviewCertification Details and CriteriaProgram FeaturesCourse CurriculumDelivery ModeCustomer ReviewsPrerequisitesAbout UsTarget AudienceKey Learning OutcomesProgram Overview:The AWS Big Data certification training prepares you for all aspects of hosting big data andperforming distributed processing on the AWS platform and has been aligned to the AWSCertified Data Analytics – Specialty exam. This course is developed by industry leaders andaligned with the latest best practices.Program Features:4.9 hours of online self-paced learning44 hours of instructor-led online trainingFour industry-based course-end projectsInteractive learning with Jupyter notebooks integrated labsDedicated mentoring session from our industry expert faculty membersDelivery Mode:Blended - Online self-paced learning and live virtual classroomPrerequisites:It is recommended that participants in this AWS Big Data Certification online course have:Basic knowledge of AWS technical essentialsFair understanding of big data and Hadoop concepts

Target Audience:This course is best suited for the following professionals:Data scientistsData engineersSolutions architectsData analystsKey Learning Outcomes:When you complete this AWS Big Data Certification course, you will be able to accomplishthe following:Understand how to use Amazon EMR for processing the data using Hadoop ecosystem toolsUnderstand how to use Amazon Kinesis for big data processing in real-timeAnalyze and transform big data using Kinesis StreamsVisualize data and perform queries using Amazon QuickSightCertification Details and Criteria:At least 85 percent attendance of one live virtual classroomA score of at least 75 percent on the course-end assessmentSuccessful evaluation of the course-end project

Course Curriculum:Lesson 01 - AWS in Big Data introductionIntroduction to Cloud ComputingCloud Computing Deployments ModelsAmazon Web Services Cloud PlatformThe Cloud Computing DifferenceAWS Cloud EconomicsAWS Virtuous CycleAWS Cloud Architecture Design PrinciplesWhy AWS for Big Data - ReasonsWhy AWS for Big Data - ChallengesDatabases in AWSRelational vs Non-Relational DatabasesData Warehousing in AWSServices for Collecting, Processing, Storing, and Analyzing Big Data1.Amazon Redshift2.Amazon Kinesis3.Amazon EMR4.Amazon DynamoDB5.Amazon Machine Learning6.AWS Lambda7.Amazon Elasticsearch Service8.Amazon EC2 (big data analytics software on EC2 instances)Amazon RedshiftAmazon KinesisAmazon EMRAmazon DynamoDBAmazon Machine LearningAWS LambdaAmazon Elasticsearch ServiceAmazon EC2 (big data analytics software on EC2 instances)Key TakeawayKnowledge ChecksLesson End Project

Lesson 02 - CollectionObjectivesAmazon Kinesis FundamentalsLoading Data into Kinesis StreamKinesis Data Stream High-Level ArchitectureKinesis Stream Core ConceptsKinesis Stream Emitting Data to AWS ServicesKinesis Connector LibraryKinesis FirehoseTransferring Data Using LambdaAmazon SQSIoT and Big DataIoT FrameworkAWS Data PipelineAWS Data Pipeline ComponentsKey TakeawayKnowledge ChecksLesson End ProjectLesson 03 - StorageObjectivesIntroduction to AWS Big Data Storage ServicesAmazon GlacierGlacier and Big DataDynamoDB IntroductionThe Architecture of the DynamoDB TableDynamoDB in AWS EcosystemDynamoDB PartitionsData DistributionLocal Secondary Index (LSI) **Global Secondary Index (GSI) **DynamoDB GSI vs LSIDynamoDB StreamCross-Region Replication in DynamoDBPartition Key SelectionSnowball & AWS Big DataAWS DMSAWS Aurora in Big DataKey TakeawayKnowledge ChecksLesson End Project

Lesson 04 - Processing IObjectivesIntroduction to AWS Big Data Processing ServicesAmazon Elastic MapReduce (EMR)Apache HadoopEMR ArchitectureStorage OptionsEMR File Storage and CompressionSupported File Format and File SizeSingle-AZ ConceptEMR OperationsEMR ReleasesAWS ClusterLaunching a ClusterAdvanced EMR Setting OptionChoosing Instance TypeNumber of InstancesMonitoring EMRResizing of ClusterUsing Hue with EMRSetup Hue for LDAPHive on EMRHive Use CasesKey TakeawayKnowledge ChecksLesson End Project

Lesson 05 - Processing IIHBase with EMRHBase Use CasesComparison of HBase with Redshift and DynamoDBHBase Architecture HBase on S3HBase and EMRFSHBase IntegrationHCatalogPresto with EMRAdvantages of PrestoPresto ArchitectureSpark with EMRSpark Use CasesSpark ComponentsSpark Integration With EMRAWS Lambda in AWS Big Data EcosystemLimitations of LambdaLambda and Kinesis StreamLambda and RedshiftKey TakeawayKnowledge ChecksLesson End ProjectLesson 06 - Analysis IObjectivesIntroduction to AWS Big Data Analysis ServicesRedShiftRedShift ArchitectureRedShift in the AWS EcosystemColumnar DatabasesRedShift Table DesignRedShift Workload ManagementRedShift Loading DataRedShift Maintenance and OperationsKey TakeawayKnowledge ChecksLesson End Project

Lesson 07 - Analysis IIMachine LearningMachine Learning - Use CasesAlgorithmsAmazon SageMakerElasticsearchAmazon Elasticsearch ServiceLoading of Data into thenaPresto and HiveIntegration with AWS GlueComparison of Athena with Other AWS ServicesLab Run Query on S3 Using Serverless AthenaKey TakeawayKnowledge ChecksLesson End ProjectLesson 08 - VisualisationObjectivesIntroduction to AWS Big Data Visualization ServicesAmazon QuickSightAmazon QuickSight - Use CasesLAB Create an Analysis with a Single Visual Using Sample DataWorking with DataAssisted Practice: TBDQuickSight VisualizationBig Data VisualizationApache ZeppelinJupyter NotebookComparison Between NotebooksD3.js (Data-Driven Documents)MicroStrategyKey TakeawayKnowledge ChecksLesson End Project

Lesson 09 - SecurityObjectivesIntroduction to AWS Big Data Security ServicesEMR SecurityRolesPrivate SubnetEncryption At Rest and In TransitRedShift SecurityKMS OverviewSloudHSMLimit Data AccessSTS and Cross Account AccessCloud TrailKey TakeawayKnowledge ChecksLesson End Project

Customer Reviews:Ajinkya GaviAssociate at CognizantI joined Simplilearn to explore more about the upcomingTechnology. Just 1 month of course along with sufficientpractice landed me a job in a Top IT MNC. I never thoughtan experienced person can start as fresher in Bigdata, butSimplilearn made it happen. Thank you Simplilearn.Angiras ModakIIM Bangalore, Executive ManagementSimplilearn’s Big Data course prepared me with the skills toget ahead in my career. The course helped me to enhancemy career from Senior Associate to Program OperationsManager at Sapient within 1 year of completing the course.Md Azhar HussainThis platform has enhanced my knowledge of big data andprovided me the opportunity to work with experiencedindustry professionals. I appreciate the tutor's in-depthknowledge and, the help and support provided bySimplilearn. After the certification, I was able to grab a rolechange.

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Amazon Web Services Cloud Platform The Cloud Computing Difference AWS Cloud Economics AWS Virtuous Cycle AWS Cloud Architecture Design Principles Why AWS for Big Data - Reasons Why AWS for Big Data - Challenges Databases in AWS Relational vs Non-Relational Databases Data Warehousing in AWS Services for Collecting, Processing, Storing, and .