Download Udemy – DuckDB – The Ultimate Guide 2024-2

DuckDB - The Ultimate Guide


DuckDB – The Ultimate Guide, the complete DuckDB training course is published by Udemy Academy. Data lakes and big data infrastructure (such as Apache Hadoop and Spark) are not optimal solutions for every data problem. DuckDB is a great solution for running a database very similar to PostgreSQL but with massive analytical capabilities, locally. duckdb Python, duckdb dbt, duckdb Streamlit, duckdb s3 & wasm & Docker and many more: you can do almost anything with it. In addition, you can easily export the data: duckdb csv, duckdb parquet, duckdb json are all ways to share your analysis results in no time. Integrating Python is as easy as doing “pip install duckdb” and you’re good to go. We will cover Python’s duckdb integration in one of the cases. Instead of having PostgreSQL/Mariadb for each developer on the team, you can set the configuration to create an in-memory instance of DuckDB. If you need to request data from the internet, no problem, Duckdb Httpfs is a package we will also study. If you want to run a columnar database locally with very large data, there really isn’t anything else like DuckDB.

You can run PySpark locally instead, but it will be more of a hassle. Duckdb Pivot can even help you create spreadsheet tables. This is a step forward for the Analytics field of SQLite. DuckDB works great when running bulk queries on limited columns while SQLite works great when querying one or more rows using filters. In the course we will compare duckdb vs. Sqlite and duckdb vs. Clickhouse. Pandas loads all data into memory and runs on a single thread. Hence it can’t work on larger memory datasets and also doesn’t use all your CPU cores. Whereas DuckDB can work on datasets larger than memory. In addition, it can distribute the load across all CPU cores. All this using the SQL language by default!

What you will learn

  • Architecture and implementation of analytics solutions that use DuckDB as a database
  • You’ll learn the basics that make DuckDB super fast on any machine (theory).
  • You will learn to work with DuckDB from the Python environment (exercise)
  • You will learn to work with DuckDB from the CLI environment (command line) (exercise)
  • Use DuckDB as a backup database for your Streamlit Python Analytics applications (exercise)
  • Combine DuckDB with dbt (Data Builder) to simplify Analytics data warehouse development (exercise)
  • You will learn to work in MotherDuck: a Cloud-native (SaaS) environment for DuckDB (exercise).
  • You will understand how DuckDB differs from other databases: both analytical (Clickhouse, Redshift, Cassandra) and OLTP (PostgreSQL, SQLITE).

Who is this course suitable for?

  • Developers and data engineers who want to learn about modern local data warehousing and develop analytics solutions faster
  • Data analysts and data scientists who want to upskill and learn how to use embedded analytic databases
  • Data professionals and enthusiasts who want to improve their skills in databases and data modeling.
  • People who want to become a Data Scientist, BI Analyst, Data Engineer or Data Analyst

Course details DuckDB – The Ultimate Guide

  • Publisher: Udemy
  • teacher : Max Migutin
  • English language
  • Education level: all levels
  • Number of courses: 72
  • Training duration: 5 hours and 3 minutes

Chapters of DuckDB – The Ultimate Guide course

Course prerequisites

  • Basic SQL is helpful but not necessary (we’ll use guides provided)
  • Basic Python
  • Laptop or PC


DuckDB - The Ultimate Guide

Sample video

Installation guide

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English subtitle

Quality: 720p

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Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 743 MB

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2.72 GB

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