DuckDB - The Ultimate Guide

Name: DuckDB - The Ultimate Guide
Price: 9 USD
Availability: InStock

5h 56m 13s

English

Paid

November 13, 2024

Why should you learn DuckDB? DuckDB is one of the fastest-growing technologies, with search queries increasing by 1200% over the past two years! This is not by chance: DuckDB offers powerful analytical capabilities similar to PostgreSQL but allows you to run local databases without complex configurations and costs.

Why Choose DuckDB?

Ease of Integration and Cost-Free: DuckDB supports a variety of integrations, such as Python, dbt, Streamlit, s3, and even Docker. Data export is available in CSV, Parquet, and JSON formats, accelerating the exchange of analysis results. Integration with Python is simple - just the command pip install duckdb!
Local Big Data Analysis: DuckDB allows running columnar databases for local analysis of large data volumes, making it an indispensable tool for analysts.
Speed: DuckDB operates 3 times faster than Pandas, allowing work with large datasets and distributing the load across all CPU cores.

This course is not just about learning DuckDB. It's a solution for fully mastering this new and rapidly growing technology!

What You Will Get After the Course:

Master the architecture and principles of DuckDB and learn how to create analytical solutions based on it
Learn to use DuckDB from Python and the command line
Apply DuckDB as a database for analytical applications on Streamlit
Master working with MotherDuck - a cloud platform for working with DuckDB
Learn how to use DuckDB in Docker and integrate it into the microservice architecture of analytical services
Master Rill - a platform based on DuckDB for creating fast dashboards and BI solutions

Join the course and find out how DuckDB can help you implement powerful analytical solutions!

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#	Title	Duration
1	Welcome!	02:19
2	What will You Learn in this Course?	02:40
3	What is DuckDB & Why is it SO COOL?	02:40
4	What is DuckDB? (detailed)	06:13
5	Why use DuckBD?	06:08
6	What role does DuckDB play in modern Analytics World?	04:16
7	DuckDB's competition & market niche	06:58
8	When should you use DuckDB? (typical use cases)	06:27
9	Who Should Use DuckDB?	02:42
10	DuckDB Installation	07:20
11	Environment configuration	07:57
12	Getting started with DuckDB's SQL	05:49
13	Outputting SQL's results into files	08:34
14	Practice Case Description	03:03
15	Importing Data	03:16
16	DuckDB SQL Innovations: SUMMARIZE & REPLACE	05:11
17	DuckDB SQL Innovations: EXCLUDE & COLUMNS & GROUP BY ALL	05:27
18	Window Functions: the DuckDB way	04:08
19	PIVOTing in DuckDB	03:14
20	TABLE Functions in DuckDB	01:55
21	Practice Case Description	01:10
22	Downloading Data	03:33
23	Duckdb and Python: Analytics workflow - part1	06:35
24	Duckdb and Python: Analytics workflow - part2	05:02
25	Duckdb and Python: Analytics workflow - part3	04:22
26	Streamlit Introduction	01:29
27	Practice Case Description	04:41
28	Fetching Data - part1	02:33
29	Fetching Data - part2	05:00
30	Launching the App	05:39
31	Data Build Tool (dbt) Introduction	01:45
32	Practice Case Description	02:47
33	Data Walkthrough	03:27
34	Fetching Data - part1	07:23
35	Fetching Data - part2	02:33
36	Running dbt Pipeline	07:18
37	DBeaver: Amazing Database Management Tool	02:47
38	DuckDB Backward Compatibility Issue: SOLVED	06:53
39	Exploring End Result: duckdb DataWarehouse	03:00
40	What is MotherDuck?	00:57
41	MotherDuck's Features	07:44
42	Attaching a Remote Database	05:55
43	Detaching a Remote Database	01:54
44	Automating Authentication to MotherDuck Platform	03:48
45	Mother Duck Updates: Summer 2024	01:06
46	Sharing Databases	06:41
47	AI in MotherDuck: Intro	04:40
48	Querying Data with Natural Language feature	04:09
49	A More Challenging Query for AI	03:38
50	Rill Intro	01:02
51	Case End Product DEMO	03:04
52	What is Rill?	03:55
53	Case Data	04:37
54	Data Sources	05:07
55	Data Models	03:44
56	Dashboard Outlining	02:42
57	UI: Part 1	05:02
58	UI: Part 2	04:34
59	Setting up a Github repo	05:06
60	Connecting Rill Cloud to Github	02:37
61	Sharing access to Dashboard	04:03
62	Scheduling Data Refresh	05:19
63	Deleting Rill Project	01:32
64	DuckDB in Data Pipelines	04:49
65	End Result: What We'll be Working Towards	02:48
66	Dagster: Intro	02:51
67	Setting up Environment	04:17
68	Data Pipeline Walkthrough: part 1	06:59
69	Data Pipeline Walkthrough: part 2	03:59
70	Launching Pipeline & Case wrapping up	05:49
71	Case Intro	01:29
72	Business Case Architecture	06:02
73	Disclaimer: Fast Forward if needed	01:10
74	Movies Data base API	04:25
75	Dockerfile: Packaging the Project	03:47
76	Managing Python Dependencies with Poetry	03:42
77	Fetching Data from API	05:55
78	Understanding Data	03:51
79	Recommender System Codebase	06:00
80	FastAPI Microservice	02:16
81	Building Docker Image	05:55
82	Exploring Data inside DuckDB	06:25
83	Getting Recommendations	05:22
84	Wrapping Up the Case	01:12