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Analytics Engineering Bootcamp

Analytics Engineering Bootcamp

Loại khoá học: Business Analytics & Intelligence

Become an Analytics Engineer expert with just ONE course. Learn Data Modelling, dbt, Google Bigquery & many more!

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50.000 VND
65 VND
Đầy Đủ Bài Giảng
Học Online Tiện Lợi
Kích Hoạt Nhanh 2-5 Phút
Thanh toán tự động
Được phép tải xuống

Tổng quan

Nội dung khoá học

Đánh giá

Mô tả

Welcome to the Analytics Engineering Bootcamp course. the only course you need to become an amazing Analytics Engineer.

This complete Analytics Engineering Bootcamp will take you step-by-step through engaging and fun lectures and teach you everything you need to know on how to succeed as an Analytics Engineer. Throughout this course you’ll get an in depth insight into all the various tools, technologies and modelling concepts.

Students will learn how to design and implement a Data Warehouse solution using DBT (Data build tool) & BigQuery.

Each section contains scenario based quiz questions that help solidify key learning objectives for each concept & theory..

By the end of the course, you'll learn and get really good understanding of:

  • Differences between database and a data warehouse

  • Concepts between OLTP & OLAP systems

  • Normalisation & De-Normalisation methods

  • Data Modelling methodologies such as (Inmon, Kimball, Data Vault & OBT)

  • Difference between ETL & ELT

  • Data modelling techniques especially using dbt

  • Hands-on experience building dimensional data warehouse

RECENT UPDATES:

Mar2023 - Updated Glossary and added more contents

Mar2024 - New: dbt Power User accelerated development lectures (Including usage of Data Pilot, Generative AI driven workflow assistant)


Who this course is for:

  • Data Analyst, BI Analysts or Data Warehouse developers who are looking to become Analytics Engineers or looking to improve existing skills

  • For data professionals who wants to get a refresher on all the concepts and terms surrounding OLTP & OLAP systems

  • Students or recent graduates who are looking to get a job as an Analytics Engineer

  • Anyone who is interested in Analytics Engineer Career Path

Bạn sẽ học được gì

Learn all the skill sets that is required to become an Analytics Engineer

In-depth understanding of data modelling techniques

Ability to participate in architectural decision making and be able to create one

Data modelling techniques using DBT

Learn hands-on skills required to build a Data Warehouse from scratch

Boost your resume with most in-demand Analytics Engineer skills

Design & Implement a data warehouse

Create Data Warehouse Architecture

Design Conceptual, Logical & Physical Models

Learn various modelling methodologies (Inmon, Kimball, Data Vault, OBT)

Apply principles of dimensional data modeling in a hands-on

Learn all the concepts and terms such as the OLTP, OLAP, Facts, Dimensions, Star Schema, Snowflake Schema

Yêu cầu

  • No prior experience is required, however, if you have some basic understanding of SQL it'll help you understand this course better

Nội dung khoá học

11 sections

Introduction

4 lectures
Introduction
08:28
Course Overview
06:08
How to get the best out of this course
03:13
Resources
00:09

What is a database?

18 lectures
Database Introduction
00:53
Database definition
04:22
SQL Example
01:49
Database Management System (DBMS)
02:57
Sheets vs Database
05:23
OLTP
04:56
OLTP ACID
06:15
OLAP
06:02
OLTP vs OLAP Summary
02:47
NoSQL Introduction
01:58
Key Value Store
02:46
Document Store
03:19
Wide Columns
03:34
Graph Database
02:10
Search Engines
00:52
SQL vs NoSQL
01:52
On-Prem vs Cloud
05:30
Quiz
15 questions

What is a data warehouse?

14 lectures
Data Warehouse Introduction
01:39
Data Warehouse Definition
08:07
Data Warehouse Benefits
06:31
Data Warehouse Architecture
07:42
Data Source
02:34
Data Lake
15:17
Data Warehouse Layer
08:40
Business Intelligence Introduction
03:28
Business Intelligence Tools
03:59
ETL - ELT Introduction
02:26
ETL
12:45
ELT
04:35
ETL vs ELT
05:07
Quiz
17 questions

Data Modelling & ERD Notations

11 lectures
Data Modelling & Entity Relationship Diagram (ERD) Introduction
01:36
Data Modelling Overview
04:19
ERD Overview
05:19
Entity Attributes Relationships
09:03
Steps to Create an ERD
02:23
Build ERD using Chen's Notation Style
07:16
Build ERD using Information Engineering Notation Style
04:02
Data Modelling Concepts
10:22
Different Type of Keys
09:41
Recommended Tools for Creating ERD
01:51
Quiz
9 questions

Normalisation & Denormalisation

9 lectures
What is Normalisation?
06:33
1st Normal Form
04:33
2nd Normal Form
02:14
3rd Normal Form
01:54
Pros & Cons of Normalised Model
01:48
What is De-Normalisation?
01:39
De-Normalisation Techniques
06:54
Pros & Cons of De-Normalised Model
03:55
Quiz
11 questions

Data Warehouse Design Methodologies

20 lectures
Data Warehouse Design Methodologies Introduction
01:14
Inmon Methodology
04:52
Corporate Information Factory (CIF) Architecture Explained
09:19
Inmon Architecture
02:15
Pros & Cons of Inmon Methodology
02:11
Kimball Methodology
01:58
Processes of Kimball Methodology
02:34
Kimball Architecture
02:30
Pros & Cons of Kimball Methodology
02:47
Inmon vs Kimball
01:41
Hybrid Architecture
02:34
Data Vault Methodology Introduction
02:53
Data Vault Components
03:18
Data Vault Architecture & Example
04:47
Pros & Cons of Data Vault
02:19
Inmon vs Kimball vs Data Vault
03:03
One Big Table (OBT) / Wide Table
04:16
Pros & Cons of OBT
02:28
Data Modelling Then, Now & Next
05:39
Quiz
18 questions

Dimensional Modelling

30 lectures
Dimensional Modelling Introduction
01:39
What is Dimensional Modelling?
01:58
Data Warehouse LifeCycle Overview
04:49
Program/Project Planning
09:52
Requirement Gathering
11:02
Concept & Steps of Dimensional Modelling
06:35
Select Business Process & Declare the Grain
06:20
Dimensions (Types)
02:15
Conformed Dimensions
02:57
Junk Dimensions
02:58
Degenerate Dimensions
03:45
Role Playing Dimensions
01:38
Slowly Changing Dimensions (SCD) - Intro
01:46
Type 0 - SCD (Slowly Changing Dimensions)
00:52
Type 1 - SCD (Slowly Changing Dimensions)
00:41
Type 2 - SCD (Slowly Changing Dimensions)
02:43
Type 3 - SCD (Slowly Changing Dimensions)
01:14
Type 4 - SCD (Slowly Changing Dimensions)
01:43
SCD - Store as Snapshots
02:40
Bridge Tables
01:29
Facts
01:57
Additive Facts
01:58
Semi-Additive Facts
01:48
Non-Additive Facts
00:56
Transaction Facts Tables
01:58
Periodic Facts Tables
02:17
Accumulative Facts Tables
02:05
Star Schema
03:57
Snowflake Schema
03:29
Quiz
18 questions

Setting up Environments

6 lectures
BigQuery Setup Introduction
05:07
BigQuery Tables Setup using CSV
03:09
BigQuery Tables Setup Using SQL Script
02:42
Setting up WSL2 for Windows
00:04
Git Repository Setup
08:23
dbt setup & Installation
19:07

(Hands-on dbt) Building dimensional data warehouse

29 lectures
Introduction
00:25
Hands-on overview
00:49
Use-Case Introduction
01:09
Use-Case Detailed Discussion
03:36
Requirements Gathering
02:16
Data Profiling - Introduction
14:31
Data Profiling - Completed
02:47
AE Workbook - Walkthrough
02:50
Bus Matrix - High Level Entities
11:31
Conceptual Model
08:40
Architecture Design
03:12
Dimensional Modelling Introduction
02:16
Bus Matrix Detailed
09:35
Source to Target Mapping (Source to BQ Data Lake)
12:21
Source to Target Mapping (BQ Data Lake to Staging)
04:14
Dimensional Model (Attributes & Measures)
09:28
Source to Target Mapping (Data Lake to Data Warehouse)
10:23
Source to Target Mapping (Data Warehouse to OBT)
02:41
Logical Model Design
08:06
Physical Model Design
14:39
dbt overview
08:33
Physical Implementation (Staging Layer)
20:46
Physical Implementation (Staging Layer) Cont.
05:14
Physical Implementation Dim Tables (Data Warehouse Layer)
26:27
Physical Implementation Fact Tables (Data Warehouse Layer)
13:51
Physical Implementation (Analytics OBT)
15:50
Debugging (dbt)
02:09
Adding Tests (dbt)
02:12
Hands-on Complete
00:41

Accelerate dbt Development with Power User for dbt (DataPilot)

14 lectures
Introduction to dbt Power User
01:28
dbt Power User pre-requisites
00:07
Installation and Configuation
10:07
Generate dbt Models from source file or SQL
04:39
Query Translation
03:28
Query Explanation
03:56
dbt Actions tool and Query results preview
06:00
Update dbt Model
04:07
Project Governance
08:04
Write dbt Tests Automatically
06:07
Impact Analysis with Column Lineage
04:42
Documentation Generation
04:44
Collaboration Workflow
05:54
Defer to prod
05:09

Glossary

1 lectures
Glossary
05:30

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