Azure Data Lake & Storage: Getting Started Guide
Working with Azure Data Lake Storage, blob storage, and data access patterns for modern data engineering workflows.
Master essential concepts through comprehensive series on Python, SQL, and cloud data processing patterns
Cloud data engineering patterns and Azure-specific implementations
Cloud data engineering patterns and Azure-specific implementations
Working with Azure Data Lake Storage, blob storage, and data access patterns for modern data engineering workflows.
Introduction to Azure Data Factory (ADF) for building and orchestrating ETL/ELT data pipelines at scale.
Master data manipulation, analysis, and visualization with Python's powerful ecosystem
Deep dive into advanced Pandas patterns, performance optimization, and complex data operations.
A comprehensive introduction to the Pandas library for data analysis and manipulation in Python.
Learn different techniques to filter and subset pandas DataFrames efficiently
Master the next-generation DataFrame library with expression-based programming, lazy evaluation, and blazing-fast performance.
Learn the fundamental differences between Pandas and Polars, understand core concepts unique to Polars, and get productive with minimal friction.
Understand Polars' strict type system, nested data structures like Arrays, Lists, and Structs, and learn the crucial differences between null and NaN for robust data pipelines.
Master advanced Polars expressions including string manipulation, datetime operations, list columns, and complex data transformations.
Learn query patterns, optimization techniques, and database best practices
Learn query patterns, optimization techniques, and database best practices
Essential SQL concepts, query structure, and fundamental patterns for data retrieval and manipulation.
Deep dive into advanced SQL concepts including Window Functions, Common Table Expressions (CTEs), and recursive queries.
Real-world code samples and use cases you can implement immediately
Techniques to make your data processing faster and more efficient
Industry standards and patterns used by data engineering professionals