18 hours of action packed Snowflake Data Engineering content including Hybrid tables, Iceberg tables and Dynamic Tables.
⏱️ Length: 18.1 total hours
⭐ 4.58/5 rating
👥 1,878 students
🔄 October 2025 update
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Course Overview
- Embark on an intensive 18-hour ‘Zero to Expert’ journey for Data Engineers to master Snowflake on AWS. This action-packed course delves into building, optimizing, and managing scalable cloud-native data platforms. You’ll harness Snowflake’s unique architecture for high performance and concurrency, progressing from foundational concepts to advanced data engineering patterns. The curriculum highlights the latest innovations, including Hybrid Tables for transactional data, Iceberg Tables for open data lake integration, and Dynamic Tables for declarative, continuous data transformations, empowering you to architect cutting-edge data solutions.
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Requirements / Prerequisites
- Basic SQL Proficiency: Familiarity with fundamental SQL commands (DDL/DML) is expected.
- Conceptual Cloud Understanding: General grasp of cloud computing principles, especially AWS, will be beneficial.
- Data Concepts Awareness: Prior exposure to basic data warehousing or ETL/ELT concepts helps contextualize.
- Snowflake Account Access: A free trial account is recommended for all hands-on labs.
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Skills Covered / Tools Used
- Advanced SQL for Data Transformations: Master optimized SQL for complex transformations leveraging Snowflake functions.
- Snowflake Architecture & Performance: Design efficient data models, manage warehouses, and apply optimizations (clustering, materialized views, search optimizations) for peak performance/cost control.
- Modern Data Lakehouse Integration (Iceberg Tables): Implement robust data lakehouse patterns; integrate Snowflake with external Apache Iceberg data for unified analytics.
- Transactional Workloads (Hybrid Tables): Develop solutions for real-time transactional analytics and mutable data operations directly in Snowflake.
- Declarative & Continuous ELT (Dynamic Tables): Automate data pipelines using Dynamic Tables for declarative transformations and continuous freshness.
- Enterprise Data Governance & Security: Implement comprehensive security frameworks: fine-grained access controls, object tagging, and data masking policies.
- Effective Cost Management & Monitoring: Understand Snowflake credit consumption, configure monitors, and optimize compute usage.
- Seamless Ecosystem Integration: Learn how Snowflake connects with BI, data science platforms, and orchestration engines via connectors/APIs.
- Complex Data Types & Schema Evolution: Master ingesting, querying, and transforming semi-structured data (JSON, XML) and managing schema changes.
- Data Sharing & Collaboration Strategies: Implement secure data sharing techniques for internal and external collaboration.
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Benefits / Outcomes
- Expert Snowflake Data Engineer: Master full Snowflake capabilities from core to advanced architecture.
- Scalable Cloud Data Solutions: Design and implement robust, high-performance, cost-efficient data warehouses/lakehouses on AWS.
- Cutting-Edge Snowflake Innovations: Gain practical expertise in Hybrid, Iceberg, and Dynamic Tables for competitive advantage.
- Optimized Data Pipelines: Develop skills in fine-tuning queries, managing resources, and automating ELT processes.
- Robust Data Governance & Security: Apply best practices for data security, access control, and compliance within Snowflake.
- Accelerated Career Growth: Enhance your profile with in-demand Snowflake expertise for advanced data engineering roles.
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PROS
- Comprehensive Coverage: “Zero to Expert” path, including Hybrid, Iceberg, and Dynamic Tables.
- Practical & Hands-on: 18 hours of action-packed content with code, slides, and data files.
- Strong Community Endorsement: Excellent 4.58/5 rating from 1,878 students.
- Current & Relevant: Features “October 2025 update.”
- AWS Contextualized: Teaches Snowflake within the crucial AWS cloud environment.
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CONS
- While ‘Zero to Expert’ for Snowflake, a general foundational understanding of data engineering concepts is beneficial for the ‘Master Class’ aspects, potentially challenging absolute newcomers to the broader data domain.
Learning Tracks: English,IT & Software,Other IT & Software