Amazon Web Services – Big Data

Big Data on AWS introduces you to cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis and the rest of the AWS big data platform. In this course, we show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Hive and Hue. We also teach you how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.Intended AudienceThis course is intended for:Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps AdministratorsData Scientists and Data Analysts interested in learning about big data solutions on AWS

Delivery MethodThis course is delivered through a mix of:Instructor-Led Training (ILT)Hands-On LabsHands-On ActivityThis course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises. Learning Objectives This course teaches you how to:Fit AWS solutions inside of a big data ecosystemLeverage Apache Hadoop in the context of Amazon EMRIdentify the components of an Amazon EMR clusterLaunch and configure an Amazon EMR clusterLeverage common programming frameworks available for Amazon EMR including Hive, Pig, and StreamingLeverage Hue to improve the ease-of-use of Amazon EMRUse in-memory analytics with Spark and Spark SQL on Amazon EMRChoose appropriate AWS data storage optionsIdentify the benefits of using Amazon Kinesis for near real-time big data processingDefine data warehousing and columnar database conceptsLeverage Amazon Redshift to efficiently store and analyze dataComprehend and manage costs and security for Amazon EMR and Amazon Redshift deploymentsIdentify options for ingesting, transferring, and compressing dataUse visualization software to depict data and queriesOrchestrate big data workflows using AWS Data Pipeline