Duckdb - The Ultimate Guide
Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.41 GB | Duration: 3h 13m
Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.41 GB | Duration: 3h 13m
Master DuckDB: Analytics Database of Future. 5 Practice Projects+Theory to learn DuckDB Python, Streamlit, CLI and more
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)
Requirements
Basic SQL is helpful but not necessary (we'll use guides provided)
Basic Python
Laptop or PC
Description
Why should I learn DuckDB?+ 1200% of searches in the last 2 yearsIts popularity is growing RAPIDLY!Data lakes and bulky Big Data Infrastructure (like Apache Hadoop & Spark) are not optimal solution to every Data problemDuckDB is an awesome solution for running a database very similar to PostgreSQL, but with HUGE Analytical Capabilities, locally without any fuss100% free & supports dozens of various integrationsduckdb 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.Ease of useRather 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.Local Analysis of BigDataIf 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.Easy to learn after SQLiteIt'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.300%+ faster than PandasPandas 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!This Course is not just a duckdb tutorial: it's a packaged solution to master this new & rapidly growing technology.Expected OutcomesAfter this Course:You will learn how to Architect & Implement Analytics Solutions that use duck db as the databaseYou will learn the underlying principles that make DuckDB so fast on any machine (Theory)You will understand how DuckDB is different from other data bases: both Analytical (Clickhouse, Redshift, Cassandra) and OLTP (PostgreSQL, SQLite)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)Use a DuckDB dbt (Data Build Tool) combo to streamline Analytics Data Warehouse development (Practice)You will learn to work in MotherDuck: a Cloud-native environment (SaaS) for duck db (Practice). You can think of it as DuckDB GUI that you might miss in CLIWhat's insideVideo lectures (with interactive annotations)PDFs with Practice Cases OutlinesDemo ResourcesFully packaged code base for Practice ProjectsFull lifetime access with all future updatesCertificate of course completion30-Day Money-Back GuaranteeThe course isn't static! I collect students' feedback and work on improving itDigital assets used:-Image from freepik with free licence from freepik dot com "Free vector gradient dynamic blue lines background"
Overview
Section 1: Course Introduction
Lecture 1 Welcome!
Lecture 2 What will You Learn in this Course?
Lecture 3 What is DuckDB & Why is it SO COOL?
Section 2: DuckDB Introduction
Lecture 4 What is DuckDB? (detailed)
Lecture 5 Why use DuckBD?
Lecture 6 What role does DuckDB play in modern Analytics World?
Lecture 7 DuckDB's competition & market niche
Lecture 8 When should you use DuckDB? (typical use cases)
Lecture 9 Who Should Use DuckDB?
Section 3: Environment Setup & Demo
Lecture 10 DuckDB Installation
Lecture 11 Environment configuration
Lecture 12 Getting started with DuckDB's SQL
Lecture 13 Outputting SQL's results into files
Section 4: CLI usage: DuckDB's Innovations in SQL
Lecture 14 Practice Case Description
Lecture 15 Importing Data
Lecture 16 DuckDB SQL Innovations: SUMMARIZE & REPLACE
Lecture 17 DuckDB SQL Innovations: EXCLUDE & COLUMNS & GROUP BY ALL
Lecture 18 Window Functions: the DuckDB way
Lecture 19 PIVOTing in DuckDB
Lecture 20 TABLE Functions in DuckDB
Section 5: Duckdb Python
Lecture 21 Practice Case Description
Lecture 22 Downloading Data
Lecture 23 Duckdb and Python: Analytics workflow - part1
Lecture 24 Duckdb and Python: Analytics workflow - part2
Lecture 25 Duckdb and Python: Analytics workflow - part3
Section 6: Streamlit + Duckdb
Lecture 26 Streamlit Introduction
Lecture 27 Practice Case Description
Lecture 28 Fetching Data - part1
Lecture 29 Fetching Data - part2
Lecture 30 Launching the App
Section 7: Duckdb + DBT
Lecture 31 Data Build Tool (dbt) Introduction
Lecture 32 Practice Case Description
Lecture 33 Data Walkthrough
Lecture 34 Fetching Data - part1
Lecture 35 Fetching Data - part2
Lecture 36 Running dbt Pipeline
Lecture 37 DBeaver: Amazing Database Management Tool
Lecture 38 DuckDB Backward Compatibility Issue: SOLVED
Lecture 39 Exploring End Result: duckdb DataWarehouse
Section 8: MotherDuck: Cloud offering of duckdb as a SaaS
Lecture 40 What is MotherDuck?
Lecture 41 MotherDuck's Features
Lecture 42 Attaching a Remote Database
Lecture 43 Detaching a Remote Database
Lecture 44 Automating Authentication to MotherDuck Platform
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