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Level Up: Advanced SQL for Data Engineering Specialization

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Coursera

Level Up: Advanced SQL for Data Engineering Specialization

Advanced SQL for Enterprise Data Engineering.

Learn production-grade SQL skills for building, securing, and optimizing enterprise data systems.

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Get in-depth knowledge of a subject
Advanced level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Advanced level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build automated ELT pipelines with advanced SQL techniques and create enterprise-grade data architectures optimized for performance and cost.

  • Design lakehouse architectures with dimensional modeling, implementing star schemas and slowly changing dimensions for scalable analytics.

  • Implement comprehensive security frameworks, role-based access controls, and Infrastructure as Code for production data systems.

  • Develop data quality governance, automated testing frameworks, and disaster recovery strategies for enterprise data reliability.

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Taught in English
Recently updated!

March 2026

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Specialization - 5 course series

What you'll learn

  • Build automated ELT pipelines with parameterized SQL and create comprehensive data flow documentation for complex multi-stage processes.

  • Optimize pipeline performance through benchmarking, partitioning strategies, and automated testing to reduce processing time and costs.

  • Implement advanced SQL techniques including window functions, MERGE operations, and data validation frameworks for enterprise systems.

  • Design data reconciliation rules and slowly changing dimension logic to maintain data integrity across multiple source systems.

What you'll learn

  • Design star and snowflake schemas with dimensional modeling principles, creating fact and dimension tables optimized for analytics.

  • Implement cost-effective data warehouse architectures with partitioning, clustering, and multi-cluster workload isolation strategies.

  • Build lakehouse data pipelines that integrate file-based storage with structured querying using external tables and modern formats.

  • Create semantic metrics layers and slowly changing dimension logic to ensure data consistency across enterprise analytics systems.

What you'll learn

  • Diagnose and resolve SQL query performance bottlenecks using execution plan analysis and advanced optimization techniques.

  • Implement comprehensive testing frameworks including unit tests, schema validation, and data quality checks for robust pipelines.

  • Build automated CI/CD workflows for database migrations and create custom functions to standardize business logic across teams.

  • Execute safe data modifications with audit trails and develop idempotent scripts that maintain data integrity in production.

What you'll learn

  • Build automated cloud data warehouses using Infrastructure as Code while implementing role-based access controls for enterprise security.

  • Diagnose and resolve database performance issues through lock contention analysis and systematic root cause investigation techniques.

  • Design cross-region disaster recovery architectures with automated failover capabilities to meet stringent business continuity requirements.

  • Optimize infrastructure costs by analyzing performance benchmarks and forecasting capacity needs for scalable data operations.

What you'll learn

  • Build automated SQL validation frameworks to detect and resolve data quality issues in production pipelines.

  • Implement comprehensive data security controls including masking, monitoring, and compliance auditing practices.

  • Create strategic roadmaps and cost-benefit models to guide data infrastructure modernization decisions.

  • Develop performance dashboards and analytics to optimize data warehouse scaling and operational efficiency.

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Instructor

Professionals from the Industry
290 Courses 43,476 learners

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