Building Batch Data Analytics Solutions on AWS (AW-BBDAS)

In this Building Batch Data Analytics Solutions on AWS course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloguing, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR.

Building Batch Data Analytics Solutions on AWS Delivery Methods

• Online

Building Batch Data Analytics Solutions on AWS

In this Building Batch Data Analytics Solutions on AWS course, you will learn how to:

• Compare the features and benefits of data warehouses, data lakes, and modern data architectures.
• Design and implement a batch data analytics solution.
• Identify and apply appropriate techniques, including compression, to optimise data storage.
• Select and deploy appropriate options to ingest, transform, and store data.
• Choose the appropriate instance and node types, clusters, auto-scaling, and network topology for a particular business use case.
• Understand how data storage and processing affect the analysis and visualisation mechanisms needed to gain actionable business insights.
• Secure data at rest and in transit.
• Monitor analytics workloads to identify and remediate problems.
• Apply cost management best practices.

Building Batch Data Analytics Solutions on AWS Prerequisites

We recommend that attendees of this course have:

• Completed the AWS Technical Essentials (AWSE) classroom course.
• One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course.