Data Analysis: SQL From Beginner to Mastery

What You Will Master in This Course

1. SQL Core Syntax (Lay a Solid Foundation for Data Query)

   Master the basic building blocks of SQL with zero jargon, and write your first valid query in 30 minutes:
   • Environment Setup: Step-by-step demos to install MySQL (the most widely used relational database) and SQL client tools (Navicat/DBeaver) on Windows/Mac, with solutions to common installation and connection problems.
   • Basic Query Syntax: Master SELECT, FROM, WHERE clauses to filter and extract the exact data you need (e.g., query sales data of a specific product in Q3).
   • Data Sorting & Grouping: Use ORDER BY to sort results, GROUP BY to aggregate data, and aggregate functions (SUM, COUNT, AVG, MAX) to calculate key metrics (e.g., total sales, average order value).
   • Advanced Filtering & Joins: Master HAVING to filter aggregated data, and JOIN (INNER JOIN, LEFT JOIN) to combine data from multiple tables (e.g., join customer table and order table to analyze customer purchase behavior).
   • Practical Exercise: Query a company’s sales database to extract monthly sales trends and top 10 best-selling products—laying the foundation for subsequent data analysis.
2. Practical Data Analysis Skills (Turn Raw Data into Business Insights)

   Learn to apply SQL to real business scenarios, and extract valuable insights that can support decision-making:
   • Data Cleaning with SQL: Master techniques to handle messy data—remove duplicates, fill in missing values, and format data to ensure data accuracy (the first step of reliable data analysis).
   • Business Scenario Queries: Solve common workplace problems with SQL:
     • Marketing: Query customer acquisition channels with the highest conversion rate to optimize marketing budgets.
     • Finance: Extract employee expense data to identify abnormal spending and control costs.
     • Operations: Analyze user retention rates to find opportunities to improve user stickiness.
   • Data Export & Visualization Preparation: Learn to export SQL query results to Excel/CSV formats, and organize data to prepare for visualization with tools like Tableau or Excel pivot tables.
   • Practical Exercise: Complete a comprehensive sales data analysis project—from data cleaning to querying key metrics, and generate a simple analysis report to present to stakeholders.
3. SQL Performance Optimization (Query Data Faster & More Efficiently)

   Master core optimization skills to avoid slow queries, especially when dealing with large datasets (a key skill for workplace competitiveness):
   • Index Fundamentals: Understand what indexes are, and learn to create effective indexes on frequently queried columns to speed up data retrieval (the most important optimization method).
   • Query Statement Optimization: Master tips to optimize SQL syntax—avoid SELECT *, reduce nested queries, and use appropriate join methods to improve query efficiency.
   • Large Dataset Handling: Learn to handle millions of rows of data efficiently—use pagination queries, avoid full table scans, and optimize database table structure to reduce query time.
   • Common Pitfalls to Avoid: Identify and fix common SQL mistakes that cause poor performance, and develop good coding habits for maintainable and efficient SQL.
   • Practical Exercise: Optimize a slow query for a large e-commerce order database, and reduce query time from minutes to seconds.