Post #1237

SQL for Data Analysts: From Basics to Advanced 🔹 Basics of SQL ➊ SQL Syntax & Basic Queries ↳ SELECT, FROM, WHERE for data retrieval ↳ Filtering data using AND, OR, BETWEEN, LIKE, IN ➋ Sorting & Limiting Data ↳ ORDER BY for sorting results ↳ LIMIT & OFFSET for pagination ➌ Data Filtering & Aggregation ↳ COUNT(), SUM(), AVG(), MIN(), MAX() ↳ Grouping data using GROUP BY and HAVING ➍ Joins & Relationships ↳ INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN ↳ Self-joins & cross-joins for complex relationships ➎ Subqueries & CTEs ↳ Writing subqueries for better query organization ↳ Using WITH to create Common Table Expressions (CTEs) 🔹 Intermediate SQL for Data Analysis ➏ Window Functions for Advanced Aggregation ↳ ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE() ↳ LEAD() & LAG() for time-based analysis ➐ String & Date Functions ↳ CONCAT(), UPPER(), LOWER(), TRIM(), SUBSTRING() ↳ DATEPART(), DATEDIFF(), EXTRACT() for date manipulation ➑ Case Statements & Conditional Logic ↳ CASE WHEN for conditional transformations ↳ Nested CASE statements for advanced logic ➒ Pivoting & Unpivoting Data ↳ PIVOT() for transforming row-based data into columns ↳ UNPIVOT() for restructuring wide tables ➓ Handling Missing Data & NULL Values ↳ Using COALESCE() & NULLIF() ↳ Filtering and replacing NULL values 🔹 Advanced SQL for Data Analysts ⓫ Optimizing SQL Queries ↳ Using Indexes to improve performance ↳ Understanding EXPLAIN & query execution plans ⓬ Recursive Queries & Hierarchical Data ↳ WITH RECURSIVE for hierarchical relationships ↳ Organizing parent-child relationships in tables ⓭ Stored Procedures & Functions ↳ Writing reusable stored procedures ↳ Creating user-defined functions (UDFs) ⓮ Working with JSON & Semi-Structured Data ↳ Extracting and parsing JSON data using JSON_VALUE() ↳ Handling nested structures in SQL ⓯ Time Series & Trend Analysis ↳ Calculating moving averages ↳ Performing time-based aggregations ⓰ SQL in Python ↳ Connecting databases using SQLAlchemy ↳ Running SQL queries in pandas.read_sql() ↳ Merging SQL and Pandas for advanced analysis 🚀The best way to master SQL is to work on real-world datasets and optimize queries for performance! Free SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v Share with credits: https://t.me/sqlspecialist Hope it helps :)