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SQL for Data Analytics
Advanced SQL patterns for data analysis and reporting.

SQL for Data Analytics π
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.
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References & Disclaimer
This content is adapted from Mastering System Design from Basics to Cracking Interviews (Udemy). It has been curated and organized for educational purposes on this portfolio. No copyright infringement is intended.
π Course Curriculum
β1. Introductionπ§Ή2. Preparing Your Dataπ3. Time Series Analysisπ₯4. Cohort Analysisπ5. Text Analysisπ¨6. Anomaly Detectionπ§ͺ7. Experiment AnalysisβοΈ8. Building Complex Data Sets
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.
