The new AWS Course will help you strengthen your data analytics strategy

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With rapid digitalization across industries, data production has increased exponentially. According to IDC, the global informationsphere (total data created over a year) was 64 ZB in 2020. It grew by 400% over the global datasphere in 2016. Organizations need a large number of IT professionals to quickly implement and manage new servers. One of the most popular options for organizations is cloud-managed analytics services. These services help them to build and maintain data pipelines. To be able to explore the new capabilities of the cloud in data analytics, data engineers must be trained. This will allow them to understand the different aspects and gain the skills necessary. AWS’ new course Building Batch Data Analytics Solutions is a popular choice because of its benefits and positioning. This article will provide more information about the course and the problems it addresses. You can also check out our AWS certification path.
What is a data pipeline? A data pipeline is a series or activities that transform the data at each step before it reaches its destination. Transforming data prepares it for data analytics and data storage processes. It is important to combine data from multiple sources in order to gain detailed insights.
What is Amazon EMR? Amazon EMR, also known as Amazon Elastic MapReduce, is a managed cluster platform that simplifies Apache Hadoop and Apache Spark. These two big data frameworks are widely used to process and analyze large amounts of data. Amazon EMR supports data professionals in transforming or moving data to the AWS cloud. Data engineers can use different analytics tools to process the data and receive the support needed in decision-making. Data lakes are used by organizations to extract more business value from data. Data pipelines allow data to be filtered and converted into reports-ready formats. Data pipelines ensure that data does not contain data noise or irrelevant data points. AWS offers a course called Building Data Lakes on AWS, which helps Data Platform Engineers and Solutions Architects understand how to secure and build data lakes in AWS. AWS Glue and Amazon Athena will be available to professionals. This course is also connected to Building Batch Data Analytics Solutions in AWS. AWS also announced the end of the Big Data on AWS course. Read our blog to learn how three AWS courses replaced the retiring Big Data course. Start your journey with our free AWS Discovery Day webinar. Explore new possibilities in data analysis through ML or AI.
NetCom Learning offers Building Batch Data Analytics Solutions on AWSNetCom Learning is an AWS Select Tier Training Partner and now offers a course that helps organizations develop better data analytics solutions in cloud. AWS launched the Building Batch Data Analytics Solutions course on AWS on April 26th 2022. Sign up for the course to learn how to create a data analysis pipeline using Amazon EMR. The course requires at least one year’s experience with open-source data frameworks. This course prepares students for the DAS-C01 AWS certified data analytics – specialty exam. Students will learn how Amazon EMR integrates to Hive, Hue and HBase as well as other open-source analytical frameworks. Students learn how to design and implement batch-data analytics solutions, as well as techniques to optimize data storage, security, monitoring analytics workloads, optimize cloud costs, and how to optimize cost in AWS.
AWS Training with NetCom LearningNetCom Learning has AWS Authorized Instructors of high quality who are highly rated and deliver the Building Batch Data Analytics Solutions for AWS course. It is a virtual instructor-led program that can be completed within one day. Practical labs are available to provide students with hands-on learning experiences. NetCom Learning is a training company that has been in business for more than 23 years. It has 3000+ certified trainers who deliver technology and business courses. We are proud to be a member of the NetCom Learning network.