Udemy – DuckDB – The Ultimate Guide 2024-10

DuckDB – The Ultimate Guide, Data lakes and bulky Big Data Infrastructure (like Apache Hadoop & Spark) are not optimal solution to every Data problem. DuckDB is an awesome solution for running a database very similar to PostgreSQL, but with HUGE Analytical Capabilities, locally without any fuss. duckdb Python, duckdb dbt, duckdb Streamlit, duckdb s3 & wasm & Docker + many more: you can almost anything with it. Additionally, you can easily do data exports: duckdb csv, duckdb parquet, duckdb json are all ways to share your analysis results in no time! Python integration is as easy as doing “pip install duckdb” & you’re ready to go! We will dive deep into duckdb Python integration in one of the cases. Rather than having a PostgreSQL/Mariadb for each developer on the team, you can setup configuration to spawn an in memory instance of DuckDB. If you need to fetch data from the Internet, it’s no problem either: Duckdb Httpfs is a package that we’ll also study.

If you want to run a columnar database locally on pretty big data, there isn’t really anything else like it. You could instead run PySpark locally but that would be much more of a headache. Duckdb Pivot can even help you create Spreadsheet-like tables. It’s a step forward to Analytics field from SQLite. DuckDB performs great when running aggregate queries on limited columns whereas SQLite works great when fetching one or more rows using filters. In the Course we will compare and contrast duckdb vs Sqlite and duckdb vs Clickhouse. Pandas loads all data into memory and runs on a single thread. Hence it can’t operate on larger than memory datasets and also doesn’t use all of your CPU cores. Whereas DuckDB can operate on datasets larger than memory. Moreover, it can distribute load across all the CPU cores. All that using SQL language by default!

What you’ll learn

• Architect & Implement Analytics Solutions that use DuckDB as the database
• You will learn the underlying principles that make DuckDB so fast on any machine (Theory)
• You will learn to work with DuckDB from Python environment (Practice)
• You will learn to work with DuckDB from CLI (command line) environment (Practice)
• Use DuckDB as a backend database for your Streamlit Python Analytics Apps (Practice)
• Combine DuckDB with dbt (Data Build Tool) to streamline Analytics Data Warehouse development (Practice)
• You will learn to work in MotherDuck: a Cloud-native environment (SaaS) for DuckDB (Practice)
• You will understand how DuckDB is different from other data bases: both Analytical (Clickhouse, Redshift, Cassandra) and OLTP (PostgreSQL, SQLITE)

Who this course is for

• Developers & Data Engineers who want to learn about modern local data warehousing and developing Analytics solutions faster
• Data Analysts & Data Scientists who want to upskill and learn how to use embedded analytics databases
• Data Professionals & Enthusiasts who want to upgrade their skills in DataBases & Data Modelling
• People that want to become a Data Scientist, BI analyst, Data Engineer or Data Analyst

Specificatoin of DuckDB – The Ultimate Guide

• Publisher : Udemy
• Teacher : Max Migutin
• Language: English
• Level : All Levels
• Lectures : 85
• Duration : 5 hours and 54 minutes

Content of DuckDB – The Ultimate Guide

Requirements

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

Pictures

Sample Clip

Installation Guide

Extract the files and watch with your favorite player

Subtitle : English

Quality: 720p

The 2024/10 version has increased the number of lessons by 13 and the duration increased by 51 minutes compared to 2024/2.

Download Links

Download Part 1 – 1 GB

Download Part 2 – 1 GB

Download Part 3 – 212 MB

File size

2.2 GB