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AWS holds 32% market share of the global cloud computing market.
Average salary of an IAM Administrator annually.
Take advantage of this extensive course that explores the nuances of AWS Elastic MapReduce (EMR) and set out on a revolutionary learning adventure. Discover the ever-changing field of big data processing while becoming an expert in using Amazon EMR to do scalable and effective data analytics. Our training offers practical experience in configuring and optimizing EMR clusters, employing Apache Hadoop and Spark, and navigating advanced capabilities like spot instances and bespoke apps, regardless of expertise level.
By dividing workloads among clusters of virtual computers, AWS Elastic MapReduce (EMR) streamlines the processing of enormous volumes of data. It is the perfect answer for big data applications as it makes use of well-known frameworks like Apache Hadoop and Apache Spark to facilitate effective data processing, analysis, and transformation at scale.
Although there aren't any particular requirements, it might help to have a basic grasp of cloud computing ideas and some experience with AWS services. Both novices and seasoned experts looking to increase their big data processing abilities can enroll in this course.
Upon successful completion of the course, you will be awarded with the course completion certificate powered by AWS from SkillUp. This certificate will be delivered to you via email within 6 hours of course completion.
Undoubtedly, with organizations depending more and more on big data processing for well-informed decision-making, AWS Elastic MapReduce capabilities are in great demand. Gaining expertise in EMR may lead to a variety of job options in cloud computing, analytics, and data engineering.
You get 90 days access to the AWS ELS course content, including video lectures, notebooks, quizzes, and supplementary resources.
Although it automates cluster creation and scaling, AWS Elastic MapReduce is not considered serverless. Even though it takes care of the infrastructure management, you still can create and personalize the clusters to meet your unique needs.