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Readme
1.
Fundamentals
1.1.
Terms to Know
1.2.
Jobs
1.3.
Skills needed
1.4.
Application Tiers
1.5.
Operational Database
1.6.
What is a Data Warehouse
1.6.1.
Data Architecture
1.6.2.
Problem Statement
1.6.3.
Key Features
1.6.4.
Need for DW
1.6.5.
Current State of the Art
1.7.
Types of Data
1.8.
Data Storage Systems
1.9.
DW 1980 - Current
1.10.
DW vs Data Mart
1.11.
DW Architecture
1.11.1.
Top-Down Approach
1.11.2.
Bottom-Up Approach
1.11.3.
Summary
1.12.
DW Characteristic
1.12.1.
Subject Oriented
1.12.2.
Integrated
1.12.3.
Time Variant
1.12.4.
Non Volatile
1.13.
Tools
1.14.
Cloud vs On-Premise
1.15.
Steps to design a DW
1.15.1.
Gather Requirements
1.15.2.
Environment
1.15.3.
Data Modeling
1.15.4.
ETL / ELT Solution
1.15.5.
Online Analytic Processing
1.15.6.
Front End
1.15.7.
Query Optimization
2.
RDBMS
2.1.
Data Model
2.1.1.
ER Model
2.1.2.
Attributes
2.1.3.
Keys
2.1.4.
Transaction
2.1.5.
ACID
2.2.
Online vs Batch
2.3.
DSL vs GPL
2.4.
Storage Formats
2.5.
File Formats
2.6.
DuckDB
2.7.
DuckDB Sample - 01
2.8.
DuckDB Sample - 02
2.9.
DuckDB - Date Dimension
2.10.
SQLBolt
3.
Cloud
3.1.
Overview
3.2.
Types
3.3.
Challenges
3.4.
AWS
3.4.1.
AWS Global Infra
3.4.2.
EC2
3.4.3.
S3
3.4.4.
IAM
3.4.5.
CloudShell
3.5.
Terraform
4.
Data Architecture
4.1.
Medallion Architecture
4.2.
Bronze to Silver
4.3.
Silver to Gold
4.4.
Sample Data from Raw to Silver
4.5.
Spark Intro
4.6.
Delta
5.
Data Warehousing Concepts
5.1.
Dimensional Modelling
5.1.1.
Star Schema
5.1.2.
Galaxy Schema
5.1.3.
Snowflake Schema
5.1.4.
Starflake Schema
5.1.5.
Star vs Snowflake
5.1.6.
GRAIN
5.1.7.
Multi-Fact Star Schema
5.1.8.
Vertabelo Tool
5.2.
Dimension - Fact
5.3.
Sample Excercise
5.4.
Keys
5.4.1.
Surrogate Keys
5.5.
More Examples
5.6.
Master Data Management
5.7.
Steps of Dimensional Modeling
5.8.
Types of Dimensions
5.8.1.
Date Dimension Table
5.8.2.
Degenerate Dimension
5.8.3.
Junk Dimension
5.8.4.
Static Dimension
5.8.5.
Conformed Dimensions
5.8.6.
SCD
5.8.6.1.
SCD - Type 0
5.8.6.2.
SCD - Type 1
5.8.6.3.
SCD - Type 2
5.8.6.4.
SCD - Type 3
5.8.6.5.
SCD - Type 4
5.8.6.6.
SCD - Type 6
5.8.6.7.
SCD - Type 5 - Fun Fact
5.8.7.
Role Playing Dimension
5.8.8.
Conformed vs Role Playing
5.8.9.
Shrunken Dimension
5.8.10.
Swappable Dimension
5.8.11.
Step Dimension
5.8.12.
Temporal
5.9.
Types of Facts
5.9.1.
Factless
5.9.2.
Transaction
5.9.3.
Periodic
5.9.4.
Accumulating Snapshot
5.9.5.
Transaction vs Periodic vs Accumulating
5.9.6.
Additive, Semi-Additive, Non-Additive
5.9.7.
Periodic Snapshot vs Additive
5.9.8.
Conformed Fact
6.
Miscellaneous
6.1.
CSV to Dimension Models Example
6.2.
Data Architecture Diagram
6.3.
Data Pipeline Models
6.4.
New DW Concepts
6.5.
Dataset Examples
6.6.
Thoughts on some data
Light
Rust
Coal
Navy
Ayu
Advance Data Warehousing
What is a Data Warehouse
Is it a Database?
Is it Big Data?
Is it the backend for Visualization?
Yes! Yes! & Yes!
