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SQL
7 Units
30 Lessons
Unit 1
Basics
Introduction to SQL Syntax and Data Types
Executing Simple SELECT Queries
Inserting, Updating, and Deleting Data Basics
Real-World Project: Building a Simple Inventory Database
Unit 2
Advanced Query Techniques
Using Aggregations and Grouping Functions
Advanced String and Date Manipulation Functions
Working with Common Table Expressions (CTEs)
Implementing Window Functions for Data Analysis
Real-World Project: Analyzing Sales Data with Advanced Queries
Unit 3
Joins and Subqueries
Understanding Inner and Outer Joins
Using Subqueries in SELECT Statements
Nesting Subqueries in WHERE and FROM Clauses
Exploring Self-Joins and Cross Joins
Real-World Project: Merging Data from Multiple Tables
Unit 4
Database Design and Normalization
Fundamentals of Database Design Principles
Applying First, Second, and Third Normal Forms
Real-World Project: Designing and Normalizing a Relational Database
Advanced Normalization Techniques like BCNF
Unit 5
Transactions and Concurrency Control
Basics of SQL Transactions and ACID Properties
Implementing Commit, Rollback, and Savepoints
Concurrency Control with Locking Mechanisms
Real-World Project: Managing Transactions in a Banking System
Unit 6
Indexing and Performance Optimization
Introduction to SQL Indexing and Its Types
Real-World Project: Optimizing a Large-Scale Database
Query Optimization Techniques and Execution Plans
Creating and Managing Indexes for Query Speed
Unit 7
Advanced Topics in SQL Integration
Integrating SQL with External Data Sources
Real-World Project: Building an Integrated SQL Application
Using Triggers and Stored Procedures for Automation
Views and Materialized Views in Complex Systems
Unit 2
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Chapter 4
Implementing Window Functions for Data Analysis
Summary
No summary available for this chapter.
Concept Check
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What is the key difference between PARTITION BY and GROUP BY in SQL window functions?
GROUP BY changes window function calculations.
PARTITION BY reduces rows like GROUP BY.
PARTITION BY does not reduce the number of rows.
PARTITION BY divides result set without reducing rows.
In the transcript, how does PARTITION BY affect the count of employees by gender?
Ignores the gender column entirely.
Adds count to each row per gender partition.
Reduces output rows for each gender.
It calculates count per partition without aggregating rows.
Why might you choose PARTITION BY over GROUP BY for data analysis?
For faster query performance only.
PARTITION BY rolls up data like GROUP BY.
To maintain original row count with partitioned calculations.
To reduce the dataset size.
What happens when using COUNT with PARTITION BY on the gender column?
Removes duplicate genders.
Counts occurrences within each gender partition.
Averages the gender values.
Sums the salaries per gender.
In SQL, how does PARTITION BY impact window function results compared to GROUP BY?
Only works with aggregate functions.
Eliminates partitions entirely.
Produces identical results to GROUP BY.
Applies function per partition without row reduction.
5 questions remaining
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Working with Common Table Expressions (CTEs)
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Real-World Project: Analyzing Sales Data with Advanced Queries