Master Foundational to Advanced SQL Concepts, including Joins, Subqueries, and Window Functions
What you will learn
What is SQL and Why is it Important?
Relational Database Management Systems (RDBMS)
Overview of Popular RDBMS: MySQL, PostgreSQL, SQL Server, and SQLite
Installing and Setting up SQL Tools and Environment
Understanding Database Structure: Tables, Rows, and Columns
Writing Your First SQL Query
Basic SQL Commands: SELECT, INSERT, UPDATE, DELETE
Sorting Data with ORDER BY
Limiting Results with LIMIT (MySQL) and FETCH FIRST (PostgreSQL)
Pattern Matching with LIKE and Wildcards
Aggregate Functions: COUNT, SUM, AVG, MIN, MAX
Grouping Data with GROUP BY and HAVING
Joining Tables: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN
Primary Keys, Foreign Keys, and Relationships
Creating, Modifying, and Deleting Databases and Tables
Indexing for Performance Improvement
Triggers and Events
Connecting SQL with Python for Automation
Using SQL with Data Visualization Tools (e.g., Tableau, Power BI).
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- Solid Data Foundation: Gain a deep understanding of data structure and storage, building a robust base for any data-related career.
- Fluent Data Communication: Develop the ability to fluently communicate with databases, precisely extracting needed information from vast datasets.
- Complex Data Synthesis: Learn to transform raw, disconnected data into meaningful, unified views by expertly navigating complex table relationships.
- Advanced Analytical Power: Master sophisticated querying techniques like nested queries and window functions for powerful aggregations and hidden pattern discovery.
- Database Architecture & Integrity: Strategically design and manage database schemas, ensuring data integrity, consistency, and optimal performance.
- Automated Data Management: Implement automated database logic via triggers, creating self-managing environments that enforce rules autonomously.
- End-to-End Data Workflow: Bridge data extraction to practical application by integrating SQL with Python and visualization tools, turning data into compelling stories.
- Analyst Problem-Solving: Cultivate a problem-solving mindset, tackling real-world data challenges through practical exercises and case studies.
- Career-Ready Portfolio: Build a comprehensive portfolio of SQL skills, positioning yourself as a highly capable professional ready for a data analyst role.
- PROS:
- Comprehensive Skill Development: Covers foundational to advanced SQL, practical tool integration, and real-world application for diverse data challenges.
- Actionable Real-World Skills: Focuses on practical application, enabling you to confidently solve business problems and derive actionable intelligence from data.
- Accelerated Career Path: Designed to equip you with essential SQL proficiency demanded by data analyst roles, significantly boosting employability.
- Structured Learning Journey: Offers a clear, step-by-step approach, making complex topics accessible for beginners while deepening intermediate users’ expertise.
- CONS:
- Significant Time Commitment: The course’s extensive coverage requires a substantial investment of time and effort to fully absorb and master all concepts.
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