SQL for Data Analytics

"@/components/blog/references";

SQL for Data Analytics 📊

Welcome to the comprehensive guide on using SQL for data analytics. This series covers everything from the basics of data preparation to advanced techniques like cohort analysis and anomaly detection.

Adapted from Mastering System Design from Basics to Cracking Interviews (Udemy) — https://www.udemy.com/course/mastering-system-design-from-basics-to-cracking-interviews/

Course Curriculum

• 1. Introduction — /blog/sql-for-data-analytics/1-introduction
• 2. Preparing Your Data — /blog/sql-for-data-analytics/2-preparing-data
• 3. Time Series Analysis — /blog/sql-for-data-analytics/3-time-series
• 4. Cohort Analysis — /blog/sql-for-data-analytics/4-cohort-analysis
• 5. Text Analysis — /blog/sql-for-data-analytics/5-text-analysis
• 6. Anomaly Detection — /blog/sql-for-data-analytics/6-anomaly-detection
• 7. Experiment Analysis — /blog/sql-for-data-analytics/7-experiment-analysis
• 8. Building Complex Data Sets — /blog/sql-for-data-analytics/8-complex-datasets

What You'll Learn

• Strategic Foundations: Understand where SQL fits in the modern data stack compared to Python/R.
• Data Preparation: Master data cleaning, profiling, and reshaping techniques.
• Advanced Analytics: Dive deep into time series, cohort behavior, and anomaly detection.
• Experimental Rigor: Use SQL to analyze A/B tests and validate hypotheses.
• Optimization: Learn best practices for code organization and complex multi-dimensional aggregation.