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Book Cover for: Getting Started with DuckDB: A practical guide for accelerating your data science, data analytics, and data engineering workflows, Simon Aubury

Getting Started with DuckDB: A practical guide for accelerating your data science, data analytics, and data engineering workflows

Simon Aubury

Analyze and transform data efficiently with DuckDB, a versatile, modern, in-process SQL database

Key Features:

- Use DuckDB to rapidly load, transform, and query data across a range of sources and formats

- Gain practical experience using SQL, Python, and R to effectively analyze data

- Learn how open source tools and cloud services in the broader data ecosystem complement DuckDB's versatile capabilities

- Purchase of the print or Kindle book includes a free PDF eBook

Book Description:

DuckDB is a fast in-process analytical database. Its ease of use, versatile feature set, and powerful analytical capabilities make DuckDB a valuable addition to the data practitioner's toolkit.

Getting Started with DuckDB offers a practical overview of DuckDB's fundamentals and guidance for effectively using its powerful capabilities. Through extensive hands-on examples, you'll learn how to use DuckDB to load, transform, and query a variety of data sources and formats, including CSV, JSON, and Parquet files, semi-structured data, remotely-hosted files, and external databases. You'll also find out how to leverage DuckDB's performance optimizations and friendly SQL enhancements. You'll explore how to use DuckDB's extensions for specialized applications, such as geospatial analysis and text search over document collections. In addition to working through examples in SQL, Python, and R, you'll also dive into using DuckDB for analyzing public datasets and discover the wider ecosystem of open-source tools and cloud services that supercharge DuckDB-powered workflows and applications.

Whether you're a seasoned data practitioner or new to working with analytical data, this book will rapidly get you up to speed with DuckDB's versatile and powerful capabilities, enabling you to apply them in your analytical workflows and projects.

What You Will Learn:

- Understand the properties and applications of a columnar in-process database

- Use SQL to load, transform, and query a range of data formats

- Discover DuckDB's rich extensions and learn how to apply them

- Use nested data types to model semi-structured data and extract and model JSON data

- Integrate DuckDB into your Python and R analytical workflows

- Effectively leverage DuckDB's convenient SQL enhancements

- Explore the wider ecosystem and pathways for building DuckDB-powered data applications

Who this book is for:

If you're interested in expanding your analytical toolkit, this book is for you. It will be particularly valuable for data analysts wanting to rapidly explore and query complex data, data and software engineers looking for a lean and versatile data processing tool, along with data scientists needing a scalable data manipulation library that integrates seamlessly with Python and R. You will get the most from this book if you have some familiarity with SQL and foundational database concepts, as well as exposure to a programming language such as Python or R.

Book Details

  • Publisher: Packt Publishing
  • Publish Date: Jun 24th, 2024
  • Pages: 382
  • Language: English
  • Dimensions: 9.25in - 7.50in - 0.79in - 1.44lb
  • EAN: 9781803241005
  • Categories: Data Science - Data VisualizationBusiness & Productivity Software - Databases

About the Author

Aubury, Simon: - Simon Aubury has been working in the IT industry since 2000 as a data engineering specialist. He has an extensive background in building large, flexible, highly available distributed data systems. Simon has delivered critical data systems for finance, transport, healthcare, insurance, and telecommunications clients in Australia, Europe, and Asia Pacific. In 2019, Simon joined Thoughtworks as a principal data engineer and today is associate director of data platforms at Simple Machines in Sydney, Australia. Simon is active in the data community, a regular conference speaker, and the organizer of local and international meetups and data engineering conferences.
Letcher, Ned: - Ned Letcher has worked as a data science and software engineering consultant since completing his PhD in computational linguistics in 2018 and currently works at Thoughtworks. He has designed and developed data-powered products and services across a range of industries and helped organizations and teams improve the effectiveness of their data processes and workflows. Ned has also worked as a Python trainer, supporting both tertiary students and data professionals across various organizations. He is active in the data community, speaking at and helping organize meetups and conferences, as well as contributing to a range of open source projects.