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  • Complete Terraform CI/CD Pipeline Setup with GitHub Actions — Beginner to Advanced

    Jan 13, 2026

    ·

    GitHub, Terraform
    Complete Terraform CI/CD Pipeline Setup with GitHub Actions — Beginner to Advanced
  • Quiz on MySQL DATE and TIME Calculations

    This content provides a quiz about MySQL date functions, testing users’ knowledge on retrieving, manipulating, and formatting date values essential for database management. Read More ⇢

    Quiz on MySQL DATE and TIME Calculations
  • Essential PySpark Concepts to Review Before Your Brillio Interview

    The content discusses interview questions and solutions at Brillio, covering topics in SQL, PySpark, AWS, and Python with example queries, processes, and explanations. Read More ⇢

    Essential PySpark Concepts to Review Before Your Brillio Interview
  • Interview Prep: Python, PySpark, and SQL Challenges

    This content provides interview questions for Data Engineer roles focusing on Python, PySpark, and SQL, along with sample solutions for common problems. Read More ⇢

    Interview Prep: Python, PySpark, and SQL Challenges
  • SQL and PySpark: Efficient String Slicing Techniques

    The content presents two code examples: one for ETL logic in SQL and another for string slicing manipulation using PySpark, demonstrating data processing techniques. Read More ⇢

    SQL and PySpark: Efficient String Slicing Techniques
  • How to Work With DATE FORMAT: Top MySQL Examples

    The content discusses various MySQL functions for date manipulation, including extraction and formatting of day, month, year, conversion of date formats, and calculations involving dates. Read More ⇢

    How to Work With DATE FORMAT: Top MySQL Examples
  • 5 SQL Queries: You Should not Miss

    The content outlines five essential SQL queries—recursive, window, self-join, aggregate filtering, and EXISTS—to improve query-writing skills for tough interviews. Read More ⇢

    5 SQL Queries: You Should not Miss
  • How to Build SQL Query: Step-by-Step Guide

    A structured method for writing SQL queries involves defining requirements, selecting key columns, planning, writing, optimizing, and testing for efficient data retrieval and modification. Read More ⇢

    How to Build SQL Query: Step-by-Step Guide
  • PySpark Code: Calculate Click Rates and Salary Matches

    The content explains PySpark code for calculating click rates and finding employees with matching salaries in the same department through self-join operations. Read More ⇢

    PySpark Code: Calculate Click Rates and Salary Matches
  • Understanding Shuffling: Key to PySpark Performance

    Shuffling in PySpark redistributes data across partitions during wide transformations like join and groupBy. Reducing shuffling enhances performance by minimizing resource usage and optimizing data processing. Read More ⇢

    Understanding Shuffling: Key to PySpark Performance
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