Data Analytics Fundamentals

via AWS Skill Builder

Overview

Embark on a detailed exploration of data analytics with the self-paced course, Data Analytics Fundamentals, offered through AWS Skill Builder. This comprehensive training covers the planning of data analysis solutions and highlights the necessary AWS services for effective data management. Throughout the course, participants will delve into basic architectures, value propositions, and extensive use cases, gaining a robust understanding of how to build and optimize data analysis frameworks using AWS solutions.

Intended Audience: Ideal for data architects, data scientists, and data analysts, this course caties to those involved in complex data handling and analysis.

Course Objectives: By the end of this course, attendees will be equipped to:

Recognize necessary data analysis solutions and identify when they are required.
Distinguish between structured, semistructured, and unstructured data.
Understand different data storage types including data lakes, AWS Lake Formation, and Amazon S3.
Explore batch and stream processing and the use of Amazon Kinesis for streaming data.
Examine various storage systems, OLTP and OLAP systems, and their databse organization impacts.
Compare row-based and columnar data storage methods and understand Amazon EMR, AWS Glue, and Amazon Redshift functionalities.
Discuss ACID and BASE compliance and the role of ETL processes.
Define data schemas and metastores, and differentiate between data and information.
Analyze data using Amazon QuickSight and Amazon Athena, understanding AWS service integration for data visualization.

Prerequisites: Participants should have:

A basic grasp of database concepts.
Foundational knowledge in data storage, processing, and analytics.
Experience with enterprise IT systems.

Delivery Method: This digital training course spans approximately 3.5 hours.

Course Outline: The curriculum includes:

Introduction to data analysis solutions.
Insights into data storage with Amazon S3 and data lakes.
Data processing methods, including batch and stream processing.
Overview of structured, semistructured, and unstructured data stores.
Discussion on data integrity, database consistency, and the ETV process.
Techniques for analyzing and visualizing data for business intelligence.
Conclusive session on integrating learned concepts and planning future steps.

Join this enriching journey into data analytics with AWS Skill Builder and enhance your skills in creating powerful data analysis solutions. Suitable for professionals engaged in data-focused roles across any sector.

Keywords: Data Analysis, AWS, Data Analytics Fundamentals, AWS Skill Builder, Data Processing, Data Storage.