Course Highlights
The AWS Data Analytics Learning Plan is designed to help learners develop essential skills in managing, analysing, and visualising data using Amazon Web Services (AWS). The curated pathway covers foundational to intermediate concepts and provides hands-on exposure to AWS Analytics Services, preparing learners for real-world data-driven roles.
Key Highlights
- Comprehensive Learning Pathway - Structured modules covering Data Collection, Storage, Processing, Analysis, and Visualization on AWS
- Foundational to Intermediate Coverage - Designed for learners with basic Cloud knowledge, progressing towards specialised Data Analytics expertise
- Role-aligned Skills - Builds competencies for roles such as Data Analyst, Business Intelligence Engineer, Data Engineer, and Cloud Data Specialist
- Self-paced, Flexible Learning - Access anywhere, anytime with interactive exercises, quizzes
- Aligned to Industry Standards - Content curated by AWS experts, aligned to industry best practices and real-world use cases
- Certification Ready - Supports preparation for AWS Certified Data Analytics - Specialty (DAS-C01)
Learning Outcome
By completing this learning plan, learners will be able to:
- Understand core AWS Data Analytics concepts and services
- Build and manage scalable data pipelines
- Analyse structured and unstructured data effectively
- Visualise insights using AWS Native BI tools
- Strengthen employability with AWS-recognised skilling credentials
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Course Details
By the end of this learning plan, learners will be able to:
- Understand Core Data Analytics Concepts
- Explain the fundamentals of Data Analytics, Data Lakes, and Data Warehousing
- Differentiate between structured, semi-structured, and unstructured data, and identify appropriate storage/processing approaches
- Explore AWS Data Analytics Services
- Gain familiarity with key AWS such as Amazon Redshift, Amazon Athena, Amazon EMR, AWS Glue, Amazon Kinesis, and Amazon QuickSight
- Understand use cases and best practices for each service within an analytics ecosystem
- Design and Build Data Analytics Solutions
- Learn to design end-to-end data pipelines for data ingestion, transformation, and analysis using AWS Native Tools
- Apply ETL (Extract, Transform, Load) processes using AWS Glue and other services
- Perform Data Analysis and Visualization
- Query data using Amazon Athena and Redshift Spectrum
- Build dashboards and visualizations in Amazon QuickSight for deriving actionable insights
- Implement Real-time and Batch Data Processing
- Configure and manage real-time data streaming pipelines using Amazon Kinesis
- Process large-scale batch data with Amazon EMR and integrate with other analytics services
- Optimise, Secure and Scale Analytics Workloads
- Apply best practices for cost optimisation, performance tuning, and scalability in AWS Analytics Solutions
- Understand Data Security, Compliance, and Governance controls within AWS Analytics Services
- Prepare for Certification and Workforce Readiness
- Align skills with industry-recognised roles such as Data Analyst, Data Engineer, and Data Scientist
- Prepare for the AWS Certified Data Analytics - Specialty exam with foundational to advanced concepts
Master In-demand Skills
- Gain expertise in AWS-powered Data Analytics services, tools, and best practices to address the growing demand for data-driven decision-making.
- Build practical skills through real-world use cases, AWS labs, and projects that will help you apply concepts directly in professional environments.
Aligned to Industry Standards
- Courses are designed and validated by AWS experts, ensuring alignment with the latest industry practices and global standards.
Future-ready Career Path
- Strengthen your career prospects by learning Advanced Analytics, Big Data, and Cloud-Native Solutions - key skills sought after across industries.
Pathway to Certification
- Prepare for AWS Data Analytics specialty certifications and validate your expertise with credentials recognised by employers worldwide.
Flexible Learning Journey
- Access structured pathways at your own pace, from foundational to advanced levels, making it suitable for both beginners and professionals.
Boost Employability
- Equip yourself with job-ready skills highly valued in roles such as Data Analyst, Business Intelligence Engineer, Data Engineer, and Cloud Solutions Architect.
The AWS Data Analytics Learning Plan is designed for professionals and learners who aim to build expertise in Data Collection, Storage, Processing, Analysis, and Visualization on AWS Cloud.
Ideal Participants:
- Data Professionals - Data Engineers, Data Analysts, BI Developers, and Data Scientists who want to design and optimise data-driven solutions using AWS.
- Cloud and IT Professionals - Cloud Engineers, Solution Architects, and System Administrators seeking to expand their skills into AWS Data Analytics Services.
- Software Developers - Developers building data-centric applications or integrating analytics into their solutions.
- Business and Functional Analysts - Professionals involved in decision-making, reporting, and insights generation using data.
- Students and Early Career Professionals - Learners from Computer Science, IT, or related domains aspiring to build careers in cloud-based Data Analytics.
- Organisations/Teams - Enterprises aiming to upskill their workforce in Cloud-Native Data Analytics for better adoption of AI/ML and business intelligence solutions.
This plan is particularly relevant for those who want to leverage AWS like Amazon Redshift, Amazon Athena, Amazon Kinesis, AWS Glue, and QuickSight to gain actionable insights and support data-driven decision-making.
Curriculum
- AWS Cloud Practitioner Essentials - Introduction to AWS Cloud, Core Services, Security, Pricing
- Introduction to Data Analytics on AWS - Core concepts of Data Lakes, Warehouses, and Analytics Tools
- Core Data Analytics Services
- Building Data Lakes on AWS
- Amazon S3, Lake Formation, Glue
- Data Ingestion and Cataloging
- Data Warehousing with Amazon Redshift
- Redshift Architecture and Workload Management
- Querying and Performance Optimization
- Data Processing with AWS Glue and AWS Lambda
- ETL Workflows and Serverless Data Processing
- Streaming Data with Amazon Kinesis
- Real-time Data Ingestion and Analytics Use Cases
- Advanced Analytics and Visualization
- Big Data Analytics Solutions on AWS
- EMR, Athena, and Integration with BI tools
- Amazon SageMaker Overview for Predictive Analytics
- Data Visualization with Amazon QuickSight
- Building Dashboards, Visual Analytics, and Sharing Insights
The AWS Data Analytics Learning Plan is designed to help learners build job-ready skills in Data Collection, Storage, Processing, Analysis, and Visualization using AWS Cloud-Native Services. The plan covers foundational to advanced topics, enabling professionals to design and implement scalable data-driven solutions.
Key Skills Gained
- Data Collection, Ingestion, and Integration Techniques
- Data Storage using Relational, Non-Relational, and Data Lake Architectures
- Data Processing (Batch and Real-time Streaming Pipelines)
- Data Analysis and Querying using SQL and AWS Native Tools
- Data Visualization and Reporting for Business Insights
- Designing Cost-effective, Scalable, and Secure Analytics Architectures on AWS
Tools and Services Covered
- Data Ingestion and Streaming: Amazon Kinesis, AWS Glue, AWS Data Pipeline
- Data Storage: Amazon S3, Amazon RDS, Amazon Redshift, Amazon DynamoDB, AWS Lake Formation
- Data Processing: AWS Glue, Amazon EMR, AWS Lambda, Amazon Athena
- Analytics and Visualization: Amazon QuickSight, Amazon Redshift Spectrum, AWS DataBrew
- Machine Learning for Analytics: Amazon SageMaker (Introductory Use Cases)
- Security and Monitoring: AWS IAM, AWS CloudTrail, AWS CloudWatch