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AWS Data Analytics Fundamentals

Last Updated: 08-03-2025

The AWS Data Analytics Fundamentals course is designed for professionals who are new to data analytics and want to understand how to use AWS cloud services to process, analyze, and visualize data. This hands-on course provides a strong foundation in data analytics concepts and introduces key AWS services like Amazon S3, Amazon Redshift, AWS Glue, and Amazon QuickSight. You will learn how to build data pipelines, perform data transformations, and create interactive dashboards to drive business insights. Whether you're working with structured or unstructured data, this course will equip you with the tools and techniques to unlock actionable insights and make data-driven decisions.

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Schedule Learners Course Fee (Incl. of all Taxes) Register Your Interest
December 20th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
10% Off
$320
$288
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December 21st
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
10% Off
$320
$288
December 22nd
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
Guaranteed-to-Run
10% Off
$320
$288
December 27th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
10% Off
$320
$288
December 28th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
10% Off
$320
$288
January 03rd
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 04th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 05th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 10th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 11th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 12th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 17th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 18th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 19th - 20th
06:00 AM - 10:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
20% Off
$320
$256
January 26th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 8 Hours)
Guaranteed-to-Run
20% Off
$320
$256

Course Prerequisites

  • No prior experience in data analytics is required, although familiarity with basic data concepts is helpful.
  • Basic knowledge of AWS services like Amazon S3, EC2, and IAM is beneficial but not mandatory.
  • Recommended: Familiarity with Excel or similar data tools is helpful but not required.

Learning Objectives

By the end of this course, you will be able to:

  1. Understand the core principles of data analytics and the data analytics lifecycle.
  2. Use Amazon S3 for data storage and management, including best practices for organizing large datasets.
  3. Process and transform data with AWS Glue, including building ETL (Extract, Transform, Load) pipelines.
  4. Set up and use Amazon Redshift for data warehousing and perform SQL-based querying to analyze structured data.
  5. Create and manage visualizations with Amazon QuickSight to derive insights from data and communicate results effectively.
  6. Automate data workflows and pipeline management using AWS Lambda and Amazon Step Functions.
  7. Understand the differences between structured, semi-structured, and unstructured data, and how AWS services handle each type.
  8. Leverage AWS security best practices to ensure the integrity, privacy, and compliance of your data.
  9. Gain a high-level understanding of machine learning basics for data analytics, with an introduction to Amazon SageMaker for predictive analytics.

Target Audience

This course is ideal for:

  • Beginners in data analytics looking to understand how to use AWS for data processing and analysis.
  • Data analysts, business analysts, and other professionals interested in learning how to work with large datasets on AWS.
  • IT professionals looking to expand their skills into the world of data analytics using cloud technologies.
  • Business leaders and decision-makers seeking to understand the role of data analytics in modern organizations.

 

Course Modules

  • Introduction to Data Analysis Solutions

    • Data Analytics and Data Analysis Concepts: Understanding the fundamentals of data analytics and the processes involved in analyzing data.
    • Challenges of Data Analytics: Exploring common challenges faced during data analytics and strategies to overcome them.
  • Data Storage (Volume)

    • Amazon S3: Learning about Amazon Simple Storage Service (S3) for scalable storage solutions.
    • Data Lakes: Understanding the concept of data lakes for storing large volumes of structured and unstructured data.
    • Data Storage Methods: Exploring various methods for storing data efficiently on AWS.
  • Data Processing (Velocity)

    • Data Processing Methods: Examining different techniques for processing data, including batch and stream processing.
    • Batch Data Processing: Understanding the process of handling large volumes of data in batches.
    • Stream Data Processing: Learning about real-time data processing and its applications.
  • Data Structure and Types (Variety)

    • Source Data Storage: Identifying various sources of data storage and their characteristics.
    • Structured Data Stores: Exploring storage options for structured data.
    • Semi-structured and Unstructured Data Stores: Understanding storage solutions for semi-structured and unstructured data types.
  • Data Cleansing and Transformation (Veracity)

    • Data Integrity: Ensuring the accuracy and consistency of data.
    • Database Consistency: Understanding the importance of maintaining consistency in databases.
    • ETL Process: Introduction to Extract, Transform, Load processes for data integration.
  • Reporting and Business Intelligence (Value)

    • Data Analysis: Techniques for analyzing data to extract meaningful insights.
    • Data Visualization: Utilizing AWS services to present data visually for better understanding and decision-making.

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