FormatMultiple choice, multiple answerTypeSpecialtyDelivery MethodTesting center or online proctored examTime180 minutes to complete the examCost300 USD (Practice exam: 40 USD)LanguageAvailable in English, Japanese, Korean, and Simplified ChineseEarn an industry-recognized credential from AWS that validates your expertise in AWS data lakes and analytics services. Build credibility and confidence by highlighting your ability to design, build, secure, and maintain analytics solutions on AWS that are efficient, cost-effective, and secure. Show you have breadth and depth in delivering insight from data. The world of data analytics on AWS includes a dizzying array of technologies and services. Just a sampling of the topics we cover in-depth are: Streaming massive data with AWS KinesisQueuing messages with Simple Queue Service (SQS)Wrangling the explosion data from the Internet of Things (IOT)Transitioning from small to big data with the AWS Database Migration Service (DMS)Storing massive data lakes with the Simple Storage Service (S3)Optimizing transactional queries with DynamoDBTying your big data systems together with AWS LambdaMaking unstructured data query-able with AWS GlueProcessing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and FlumeApplying neural networks at massive scale with Deep Learning, MXNet, and TensorflowApplying advanced machine learning algorithms at scale with Amazon SageMakerAnalyzing streaming data in real-time with Kinesis AnalyticsSearching and analyzing petabyte-scale data with Amazon Elasticsearch ServiceQuerying S3 data lakes with Amazon AthenaHosting massive-scale data warehouses with Redshift and Redshift SpectrumIntegrating smaller data with your big data, using the Relational Database Service (RDS) and AuroraVisualizing your data interactively with QuicksightKeeping your data secure with encryption, KMS, HSM, IAM, Cognito, STS, and moreAbilities Validated by the CertificationDefine AWS data analytics services and understand how they integrate with each otherExplain how AWS data analytics services fit in the data life cycle of collection, storage, processing, and visualizationRecommended Knowledge and ExperienceAt least 5 years of experience with data analytics technologiesAt least 2 years of hands-on experience working with AWSExperience and expertise working with AWS services to design, build, secure, and maintain analytics solutions
