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所在平台: Udemy |
课程主页: https://www.udemy.com/course/aws-certified-data-analytics-specialty-210-unique-ques/
课程评论：没有评论
课程名称：AWS认证数据分析 - 专业级 210+独特试题 概述： 此课程为学员提供在AWS平台上获得的数据分析专业认证，帮助学员验证其在数据湖和数据分析服务方面的专业能力。通过本认证，学员可以展现自己设计、构建、安全管理高效且具有成本效益的分析解决方案的能力，从而提升自身的可信度和信心。 课程内容广泛，涵盖AWS数据分析相关的多种技术和服务，主要包括： - 使用AWS Kinesis进行大规模数据流处理 - 利用简单队列服务（SQS）进行消息排队 - 处理物联网（IoT）产生的数据爆炸 - 通过AWS数据库迁移服务（DMS）进行小数据到大数据的迁移 - 使用简单存储服务（S3）存储大规模数据湖 - 使用DynamoDB优化事务查询 - 利用AWS Lambda将大数据系统连接起来 - 使用AWS Glue使非结构化数据可查询 - 通过弹性MapReduce处理无限规模的数据，包括Apache Spark、Hive、HBase、Presto、Zeppelin、Splunk和Flume - 针对大规模数据应用神经网络，使用深度学习、MXNet和Tensorflow - 通过Amazon SageMaker应用高级机器学习算法 - 实时分析流数据，使用Kinesis Analytics - 处理PB级数据的搜索与分析，使用Amazon Elasticsearch Service - 通过Amazon Athena查询S3数据湖 - 托管大规模数据仓库，使用Redshift和Redshift Spectrum - 使用关系数据库服务（RDS）和Aurora将小数据整合入大数据 - 通过Quicksight进行交互式数据可视化 - 使用加密、KMS、HSM、IAM、Cognito、STS等手段确保数据安全 认证能力验证： - 定义AWS数据分析服务并理解其相互集成 - 解释AWS数据分析服务在数据生命周期中的角色，包括数据收集、存储、处理和可视化 推荐知识和经验： - 至少5年数据分析技术经验 - 至少2年AWS实际操作经验 - 有设计、构建、安全管理分析解决方案的AWS服务经验 考试信息： - 形式：多项选择，多个答案 - 类型：专业级 - 交付方式：测试中心或在线监考考试 - 时间：180分钟完成考试 - 成本：300美元（练习考试：40美元） - 语言：提供英语、日语、韩语和简体中文选项 通过此课程，学员将获得行业认可的AWS认证，为今后的职业发展打下坚实基础。
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
