In this self-paced course, you will learn about the process for planning data analysis solutions and the various data analytic processes that are involved. This course takes you through 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. The course introduces you to the AWS services and solutions to help you build and enhance data analysis solutions.
You will learn about:
- Identifying data analytics challenges
- Data storage and the challenges of volume
- Data processing and the challenges of velocity
- Data structure and types, and the challenges of variety
- Data cleansing and transformation, and the challenges of veracity
- Reporting and business intelligence, and the challenges of value
The Amazon Web Services (AWS) services covered in this course include Amazon Simple Storage Service (Amazon S3), AWS Lake Formation, Amazon Redshift, AWS Glue, Amazon EMR, Amazon Kinesis, and many more.