AWS Data Analytics and Processing

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Overview

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The **Data Analytics and Processing on AWS** course is designed to provide learners with a comprehensive understanding of AWS services used for data analytics, big data processing, data integration, and visualization. This course introduces the core AWS analytics services that enable organizations to ingest, process, analyze, and visualize large volumes of data, helping them build scalable, data-driven solutions in the cloud. The course covers key services such as Amazon Redshift for data warehousing, Amazon EMR for big data processing, Amazon Kinesis Data Streams and Amazon Data Firehose for real-time data ingestion, AWS Glue for data integration and ETL, Amazon Athena for serverless data querying, Amazon QuickSight for business intelligence and visualization, and Amazon OpenSearch Service for search and analytics. Learners will also gain hands-on experience performing ETL operations using AWS Glue and querying data using Amazon Athena through practical demonstrations. This course is structured into two modules, each containing lessons and video lectures. Learners will engage with approximately **4–6 hours** of video content, combining conceptual understanding with practical demonstrations of AWS analytics and data processing services. Each module includes quizzes to reinforce learning and validate understanding of key concepts. **Course Modules:** **Module 1:** Data Analytics and Processing Services on AWS **Module 2:** AWS Data Integration, Analytics, and Visualization By the end of this course, a learner will be able to: * Understand the core AWS services used for data analytics and big data processing. * Process large-scale datasets using Amazon EMR and Amazon Redshift. * Implement real-time data ingestion using Amazon Kinesis Data Streams and Amazon Data Firehose. * Build and automate ETL pipelines using AWS Glue. * Query data efficiently using Amazon Athena. * Create interactive dashboards and visualizations using Amazon QuickSight. * Implement search and analytics solutions using Amazon OpenSearch Service. * Apply AWS best practices for building scalable and efficient analytics workflows. This course is ideal for data engineers, data analysts, cloud engineers, solutions architects, and IT professionals looking to develop foundational skills in AWS analytics and data processing services. It also provides the knowledge required to build modern analytics solutions and supports preparation for AWS data engineering and analytics-focused roles.

Syllabus

Data Analytics and Processing Services on AWS

In this section, you'll build a strong foundation in AWS data processing and streaming services, learning how to process, analyze, and move large volumes of data using AWS managed analytics solutions. You'll begin by exploring Amazon Redshift and Amazon EMR, gaining an understanding of how AWS supports data warehousing and big data processing for scalable analytics workloads. Through guided demonstrations, you'll gain hands-on experience launching Amazon EMR clusters, submitting processing jobs, and validating the results. As you progress, you'll discover AWS streaming services and learn how AWS Kinesis, Amazon Kinesis Data Streams, and Amazon Data Firehose enable real-time data ingestion, processing, and delivery. You'll also explore AWS Glue and understand how it simplifies serverless data integration, transformation, and ETL workflows for analytics applications. By the end of this section, you'll have a solid understanding of AWS data processing, streaming, and integration services, enabling you to build scalable data pipelines and support modern analytics workloads on AWS.

Building Data Analytics Solutions on AWS

In this section, you'll build a strong foundation in AWS data integration, analytics, and visualization services, learning how to transform, query, analyze, and visualize data using AWS managed analytics solutions. You'll begin by exploring AWS Glue and gain hands-on experience creating Glue Crawlers, running ETL jobs, and validating transformed data to automate data integration workflows. As you progress, you'll discover Amazon Athena and learn how to perform serverless SQL queries on data stored in Amazon S3. Through guided labs, you'll gain practical experience querying datasets and analyzing data without managing infrastructure. You'll also explore Amazon QuickSight to create interactive dashboards and business intelligence visualizations for data-driven decision-making. The section further introduces Amazon OpenSearch Service, enabling you to search, analyze, and visualize large volumes of structured and unstructured data for operational analytics and monitoring. By the end of this section, you'll have a solid understanding of AWS data integration, querying, analytics, and visualization services, enabling you to build end-to-end analytics solutions on AWS.