Dimensional Data Modeling on AWS
- Duration: 40 Hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
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Course Overview
The Dimensional Data Modeling on AWS Course is crafted for data professionals seeking to deepen their understanding of dimensional data design and its implementation using AWS technologies. This course covers foundational and advanced concepts in dimensional modeling, including star and snowflake schemas, fact and dimension tables, and best practices for data warehouse design. Participants gain hands‑on exposure to applying these principles within AWS environments to support scalable analytics and improved decision‑making frameworks.
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Course Details
- Master core dimensional modeling techniques and schema strategies
- Understand design considerations for data warehousing and analytics
- Apply star and snowflake schema principled design in AWS contexts
- Gain practical insight into AWS data stack integration with model architectures
- Enhance analytical data solutions with performance and scalability focus
- Prepare for advanced roles in data engineering and BI environments
- Ideal for data engineers, BI developers, analytics professionals, and database designers
- Familiarity with core database concepts and SQL recommended
- Foundational understanding of AWS data services (e.g., Redshift, S3) beneficial
- No mandatory certification prerequisites; hands on experience enhances learning outcomes
- Explain the principles and value of dimensional data modeling
- Differentiate between schema types and their applicability
- Define and design fact and dimension tables supporting analytical workloads
- Implement dimensional schemas for AWS data warehouses
- Integrate data modeling with AWS services to support ETL/ELT pipelines
- Integrate data modeling with AWS services to support ETL/ELT pipelines
- Introduction to dimensional modeling fundamentals
- Schema design paradigms: star and snowflake
- Fact table design and grain definition
- Dimension table structures and role of attributes
- AWS data warehousing context (e.g., Amazon Redshift, S3)
- Integration with ETL/ELT processes for analytical pipelines
- Hands on modeling exercises and real world data scenarios
Beyond Training | Our Learning Community in Action
We regularly host alumni meetups, expert sessions, and networking events to help professionals stay updated, connected, and industry-ready even after course completion.
“ Alumni meetups that keep professionals connected, visible, and engaged even after completing their training journey. ”
“ Learner gatherings designed to strengthen peer connections, real-world networking, and shared growth opportunities. ”
“ Expert-led sessions that help professionals stay updated with practical insights, trends, and industry perspectives. ”
“ A growing community experience built around collaboration, industry readiness, and continuous professional development. ”
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