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Explore subqueries, CTEs, CASE expressions, and advanced SQL logic.
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Apply ranking, aggregate, and value-based window functions.
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Analyze imported and cleaned data in a practical SQL Server project.
Strengthen your SQL skills by learning advanced querying techniques used to analyze, transform, and interpret data in SQL Server. This course begins with environment setup and common SQL mistakes, including query processing order, integer division, NULL handling, divide-by-zero errors, aggregate functions, and set operators.
You will then explore conditional logic with CASE expressions before progressing to scalar, multi-row, nested, and correlated subqueries. You will also learn how to use derived tables, EXISTS, NOT EXISTS, and multi-level common table expressions to organize and simplify complex queries.
The course introduces advanced window functions for calculating, ranking, and comparing data across related rows. You will work with ROW_NUMBER, RANK, DENSE_RANK, NTILE, PERCENT_RANK, ROWS BETWEEN, LAG, LEAD, FIRST_VALUE, and LAST_VALUE.
Finally, you will apply your knowledge in a practical SQL capstone project. You will import and clean data in SQL Server before using advanced queries to explore the dataset and answer a series of analytical questions.
This course is designed for SQL developers, database developers, data analysts, business intelligence analysts, reporting analysts, backend developers, and database administrators who want to improve their querying and data analysis skills. It is also suitable for professionals who already understand basic SQL and want practical experience with subqueries, CTEs, window functions, data cleaning, and advanced SQL Server analysis.
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Explain SQL query processing order and avoid common calculation errors
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Apply CASE expressions to implement conditional query logic
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Construct scalar, multi-row, nested, and correlated subqueries
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Organize complex queries using derived tables and multi-level CTEs
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Analyze related rows using ranking, aggregate, and value window functions
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Import, clean, and explore data using advanced SQL techniques