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AI-Powered Automation Test Engineer Program

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Course Content

Phase 1: Modern Data Warehousing Cloud Foundations
Compare OLTP/OLAP and legacy vs. cloud-native warehouses. Master Snowflake architecture, virtual warehouses, and setup.

Phase 2: Core Database Query Engineering
Create databases, schemas, tables, and views with DDL/DML. Handle date/time functions and semi-structured data like JSON.

Phase 3: Performance Optimization Architecture Tuning
Implement micro-partitioning, clustering keys, and query pruning. Tune for cost-efficiency in high-scale environments.

Phase 4: Continuous Data Pipelines Automation
Build Streams, Tasks, Snowpipe for real-time ingestion. Schedule dependencies for automated enterprise workflows.

Phase 5: Data Sharing, Security & Governance
Configure provider-consumer shares and secure data access. Set roles, privileges, and resource monitors for compliance.

Phase 6: Enterprise Integration & Industry Comparison
Load from S3/Azure and compare with Redshift/BigQuery. Prep for Snowflake certification and emerging features.

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