Course Overview
Learn about planning data analysis solutions and the various data analytic processes that are involved. Data Analytics Fundamentals on AWS covers five key factors that indicate the need for specific AWS services in collecting, processing, analyzing, and presenting your data. This includes learning basic architectures, value propositions, and potential use cases. You will be introduced to AWS services and solutions to help you build enhanced data analysis solutions.
Who should attend
- Data architects
- Data scientists
- Data analysts
Course Objectives
During this event, you will learn how to:
- Identify the characteristics of data analysis solutions and which ones indicate such a solution may be required
- Define types of data, including structured, semi-structured, and unstructured
- Define data storage types such as data lakes, AWS Lake Formation, data warehouses, and the Amazon Simple Storage Service (Amazon S3)
- Analyze batch and stream processing to understand characteristics and differences
- Define how different solutions for data streaming including Amazon Kinesis are used to process streaming data
- Analyze the characteristics of different storage systems for source data
- Analyze the characteristics of online transaction processing (OLTP) and online analytical processing (OLAP) systems and their impact on the organization of data within these systems
- Analyze the differences between row-based and columnar data storage methods