Overview

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You will build, optimize, and troubleshoot enterprise-grade data pipelines using advanced SQL techniques. This hands-on course combines data transformation, performance analysis, and system integration skills to prepare you for senior data engineering roles. You'll gain practical experience with automated ELT processes, window functions for complex analytics, and data validation frameworks that ensure pipeline reliability. The course covers real-world scenarios like reconciling conflicting data sources, implementing slowly changing dimensions, and optimizing query performance across different storage architectures. What sets this course apart is its focus on production-ready skills. You'll work with actual pipeline scenarios, benchmark competing designs, and create reusable automation scripts. By completion, you'll confidently handle the data transformation challenges that senior engineers face daily. This integrated approach bridges the gap between basic SQL knowledge and advanced data engineering expertise, positioning you for roles in data architecture, pipeline optimization, and enterprise analytics infrastructure.

Syllabus

Parameterized ELT Jobs - Foundation

You will learn the fundamentals of building automated data processing workflows using parameterized SQL, transforming static queries into dynamic, reusable pipeline components.

Pipeline Analysis & Documentation - Core Application

You will learn systematic approaches to analyzing complex data pipelines, tracing data lineage, and documenting transformation logic for enterprise-scale data infrastructure maintenance and troubleshooting.

Pipeline Performance Evaluation and Benchmarking

You will learn evidence-based pipeline performance evaluation by systematically measuring execution metrics, analyzing runtime statistics, and making data-driven optimization decisions.

Automated Pipeline Optimization

You will develop automation skills to create scripts that read configuration specifications and generate complete data transformation models, enabling scalable and consistent pipeline development.

Data Normalization with UNPIVOT - Foundation

You will learn UNPIVOT to normalize datasets and should know basic SQL; familiarity with analytical concepts is helpful but not required.

Window Functions for Rolling Metrics - Core Application

You will implement sophisticated window functions to calculate rolling averages, ranking metrics, and time-series analysis that power enterprise analytical dashboards and reporting systems.

Data Validation and Reconciliation Foundation

You will learn automated checksum validation techniques to systematically verify data transformation accuracy and flag discrepancies before they impact downstream systems.

Reusable Historical Change Tracking

You will architect modular SCD2 (Slowly Changing Dimension Type 2) logic that can be deployed across multiple dimensional tables to systematically track historical changes with enterprise-grade reliability.

Apply SQL MERGE for upsert operations

You will learn SQL MERGE statement implementation for atomic upsert operations on target tables in enterprise data integration scenarios.

Analyze field conflicts and design reconciliation rules

You will systematically analyze field-level data conflicts from multiple sources and design comprehensive reconciliation rules for reliable data integration.

Evaluate integration performance and recommend tuning

You will systematically evaluate data integration performance metrics and develop targeted tuning recommendations for optimizing system efficiency.

Batch Processing Data Transformation

You will learn systematic approaches to transforming massive volumes of semi-structured JSON data into queryable, analysis-ready formats using enterprise-scale batch processing techniques.

Workload Pattern Analysis and Optimization

You will learn systematic approaches to analyzing database workload patterns, identifying optimization opportunities, and designing intelligent partitioning and clustering strategies that dramatically improve query performance while reducing operational costs.

Performance Evaluation and Migration Strategy

You will learn comprehensive performance evaluation methodologies, conduct rigorous comparison analysis between storage architectures, and develop data-driven migration strategies that optimize enterprise database investments through quantitative business justification.

Project: Advanced SQL for Data Pipeline Optimization

You create a comprehensive data pipeline optimization system that integrates SQL automation, performance analysis, and data transformation techniques. This project combines advanced SQL skills with pipeline engineering practices to build, analyze, and optimize production-ready data workflows.