SQL for Data Analysis: Querying and Managing Databases

Data Analytics and Business Intelligence October 25, 2025
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Introduction

This comprehensive course provides essential SQL skills for data analysis and database management. Participants will learn to write complex queries, manipulate data, and optimize database performance for analytical purposes. The curriculum covers both fundamental and advanced SQL concepts including joins, subqueries, window functions, and stored procedures. Through hands-on exercises with real datasets, learners will develop the ability to extract meaningful insights from relational databases efficiently and accurately.

Objectives

Key learning objectives include:

  • Write efficient SQL queries for data extraction
  • Master complex JOIN operations across multiple tables
  • Implement subqueries and common table expressions
  • Utilize window functions for advanced analytics
  • Optimize query performance and indexing
  • Create and manage database views
  • Handle data manipulation and transaction control
  • Design queries for business reporting needs

Target Audience

  • Data analysts and business analysts
  • Database administrators
  • Business intelligence professionals
  • Data scientists needing SQL skills
  • IT professionals working with databases
  • Marketing and operations analysts
  • Students pursuing data careers

Methodology

The course emphasizes hands-on learning through extensive coding exercises and real-world database scenarios. Participants work with sample databases from various industries to solve practical business problems. Case studies focus on complex query challenges, while group activities encourage collaborative problem-solving. Individual exercises build coding proficiency, and mini-case studies present specific data extraction requirements. Syndicate discussions explore different approaches to query optimization and database design.

Personal Impact

  • Enhanced ability to write complex SQL queries efficiently
  • Improved understanding of database structures and relationships
  • Stronger data manipulation and transformation skills
  • Increased confidence in handling large datasets
  • Better problem-solving skills for data extraction challenges
  • Developed ability to optimize query performance

Organizational Impact

  • Faster and more reliable data access for reporting
  • Reduced dependency on IT for data extraction tasks
  • Improved data quality through better query design
  • Enhanced analytical capabilities across departments
  • Standardized data retrieval processes
  • Better utilization of database resources

Course Outline

Unit 1: SQL Fundamentals

Database Concepts
  • Relational database principles
  • SQL syntax and basic commands
  • SELECT statement fundamentals
  • Filtering and sorting data
Basic Query Operations
  • WHERE clause conditions
  • ORDER BY and LIMIT clauses
  • Working with NULL values
  • Column aliases and expressions

Unit 2: Data Aggregation and Grouping

Aggregate Functions
  • COUNT, SUM, AVG functions
  • MIN and MAX operations
  • GROUP BY clause implementation
  • HAVING clause for filtered aggregation

Unit 3: Advanced Joins and Subqueries

Table Relationships
  • INNER JOIN and OUTER JOIN operations
  • Self-joins and cross joins
  • Multiple table relationships
  • Join optimization techniques
Subquery Techniques
  • Correlated and non-correlated subqueries
  • EXISTS and NOT EXISTS operators
  • Subqueries in SELECT and WHERE clauses
  • Common Table Expressions (CTEs)

Unit 4: Advanced SQL Functions

Window Functions
  • ROW_NUMBER and RANK functions
  • LAG and LEAD for time series analysis
  • Running totals and moving averages
  • PARTITION BY for grouped calculations
String and Date Functions
  • String manipulation techniques
  • Date and time calculations
  • Pattern matching with LIKE
  • Data type conversion functions

Unit 5: Data Modification and Management

DML Operations
  • INSERT, UPDATE, DELETE statements
  • Transaction control with COMMIT/ROLLBACK
  • Data integrity constraints
  • Bulk data operations

Unit 6: Performance Optimization

Query Optimization
  • Execution plan analysis
  • Indexing strategies for performance
  • Query tuning techniques
  • Best practices for large datasets

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