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Data Science Analytical Interview Preparation Handbook

CI HTML Validate Markdown Links Notebooks to Markdown

This repository provides a comprehensive handbook designed to assist in preparing for data science analytical interviews, with a specific focus on Meta.

🌐 GitHub Pages

The GitHub Pages for this repository is available at: Data Science Analytical Handbook

📁 Repository Content and Structure

This repository is organized into the following sections:

Core Content

Section Location Description
Main Handbook Data-Science-Analytical-Interview-Preparation-Handbook.MD Comprehensive guide to Meta's data science interview process
Jekyll Pages _pages/ Web-ready content for GitHub Pages site
Hands-On Projects Analytical-HandsOn-Projects/ Practical data analysis projects
Simulations Simulations/ Interactive statistics notebooks

Supplementary Materials

Resource Location Description
21-Day Prep Guide supplementary/21-day-prep-guide.md Structured interview preparation plan
SQL Example Problems supplementary/sql-example-problems.md Complex SQL problems for practice
Statistics Examples supplementary/statistics-probability-example-questions.md Statistics and probability practice questions
Advanced SQL Patterns supplementary/Advanced-SQL-Patterns+Techniques.md Advanced SQL techniques and patterns
Behavioral Interview supplementary/behavioral-mock-interview.md Behavioral interview preparation guide
Key Insights supplementary/key-insights-tips-meta.md Meta-specific tips and insights

Best Practices (Data Engineering)

Topic Location
Strategy & Architecture Best-Practices/Deep_Dive/1_Strategy+Architecture.md
Data Architecture Best-Practices/Deep_Dive/2_Data_Architecture.md
Data Governance Best-Practices/Deep_Dive/3_Data_Governance.md
Version Control Best-Practices/Deep_Dive/4_Version_Control.md
Data Quality Management Best-Practices/Deep_Dive/5_Data_Quality_Management.md
Data Storage Management Best-Practices/Deep_Dive/6_Data_Storage_Management.md
ETL Processing Frameworks Best-Practices/Deep_Dive/7_ETL_Processing_Frameworks.md
Orchestration & Workflow Best-Practices/Deep_Dive/8_Orchestration_Workflow_Fundamentals.md
Data Transformation Best-Practices/Deep_Dive/9_Transformation_Fundamentals.md
Data Acquisition & Ingestion Best-Practices/Deep_Dive/Data_Acquisition_and_Ingestion.md

🚀 How to Use This Material

  1. Start with the Handbook: Begin by reading Data-Science-Analytical-Interview-Preparation-Handbook.MD for a comprehensive overview.

  2. Follow the 21-Day Prep Guide: Use supplementary/21-day-prep-guide.md for a structured preparation plan.

  3. Review Foundational Knowledge: Study statistics concepts in supplementary/statistics-probability-example-questions.md.

  4. Practice SQL: Work through problems in supplementary/sql-example-problems.md.

  5. Run Interactive Simulations: Explore Jupyter notebooks in Simulations/ for hands-on statistics practice.

  6. Prepare for Behavioral Questions: Review supplementary/behavioral-mock-interview.md.

  7. Visit the Website: Explore the full content at GitHub Pages.

🤝 Contributing

This handbook is a collaborative effort, and contributions are welcome! If you have suggestions, find errors, or want to add more content, please feel free to open an issue or submit a pull request.

📄 License

See LICENSE for details.