Dive into efficient data handling with 'In-Memory Analytics with Apache Arrow.' This book explores Apache Arrow, a powerful open-source project that revolutionizes how tabular and hierarchical data are processed. You'll learn to streamline data pipelines, accelerate analysis, and utilize high-performance tools for data exchange. What this Book will help me do Understand and utilize the Apache Arrow in-memory data format for your data analysis needs. Implement efficient and high-speed data pipelines using Arrow subprojects like Flight SQL and Acero. Enhance integration and performance in analysis workflows by using tools like Parquet and Snowflake with Arrow. Master chaining and reusing computations across languages and environments with Arrow's cross-language support. Apply in real-world scenarios by integrating Apache Arrow with analytics systems like Dremio and DuckDB. Author(s) Matthew Topol, the author of this book, brings 15 years of technical expertise in the realm of data processing and analysis. Having worked across various environments and languages, Matthew offers insights into optimizing workflows using Apache Arrow. His approachable writing style ensures that complex topics are comprehensible. Who is it for? This book is tailored for developers, data engineers, and data scientists eager to enhance their analytic toolset. Whether you're a beginner or have experience in data analysis, you'll find the concepts actionable and transformative. If you are curious about improving the performance and capabilities of your analytic pipelines or tools, this book is for you.
