Getting Started with DuckDB
A practical guide for accelerating your data science, data analytics, and data engineering workflows
Created by Simon Aubury, Ned Letcher
Explore how to work efficiently with large datasets using DuckDB. You'll learn to load, query, and transform data from various formats, and integrate these skills into your analytics or engineering projects. Practical examples in SQL, Python, and R help you quickly apply what you learn to real-world scenarios.
Packt | Jun 2024 | 382 min
What You Will Learn
You will build hands-on skills by working through real data analysis and processing tasks using DuckDB. By following practical examples, you'll learn to normalize, transform, and model data, and see how DuckDB fits into your existing workflows. Each concept is reinforced with step-by-step exercises using familiar programming languages.
Key Features
- Quickly load, transform, and analyze data from CSV, JSON, and Parquet files
- Apply SQL, Python, and R to streamline data analysis and processing tasks
- Integrate DuckDB with open source tools and cloud services for flexible workflows
Target Audience
This content is ideal for data analysts, engineers, and scientists who want to speed up their data workflows and handle complex datasets with ease. If you already know some SQL and have experience with Python or R, you'll be able to quickly put these techniques into practice and expand your toolkit for data-driven projects.
