Transform Data: SQL Window Functions

Overview

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Master the advanced SQL techniques that separate proficient data engineers from the experts. This course transforms your ability to reshape complex data structures and compute sophisticated analytical metrics that power enterprise data pipelines. This Short Course was created to help data management and engineering professionals accomplish seamless data transformation and advanced analytical computations. By completing this course, you'll be able to confidently normalize wide-format data structures, implement complex window functions for time-series analysis, and optimize data pipeline performance across major cloud platforms including Azure Synapse, SQL Server, Teradata, and Snowflake. By the end of this course, you will be able to: Analyze the transformation of pivoted data into a normalized format and its associated trade-offs Apply SQL window functions to compute rolling and rank-based metrics This course is unique because it bridges the gap between basic SQL operations and enterprise-grade data transformation techniques, providing hands-on experience with real-world scenarios that mirror production data engineering challenges. To be successful in this project, you should have a background in intermediate SQL, experience with data warehousing concepts, and familiarity with at least one enterprise database platform.

Syllabus

Module 1: Data Normalization with UNPIVOT - Foundation

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

Module 2: Window Functions for Rolling Metrics - Core Application

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