Course Content
Subtitle Guide – Hướng dẫn thêm phụ đề
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01 – Intro
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001 Welcome!
02:28
002 How this course works
04:26
003 What do you learn in this course
02:57
02 – Data Warehouse Basics
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001 Why a data warehouse
04:42
002 What is a data warehouse
04:19
003 What is Business Intelligence
02:47
004 Data Lake or Data Warehouse
06:23
005 Demos & Hands-on
02:40
006 Setting up Pentaho (ETL tool)
03:57
007 Setting up PostgreSQL (Database system)
06:35
03 – Data Warehouse Architecture
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001 3 Layers of a Data Warehouse
06:27
002 Staging area
07:22
003 Demo Setting up the staging area
03:39
004 Data Marts
06:27
005 Relational databases
06:23
006 In-Memory databases
06:48
007 Cubes
07:47
008 Operational Data Storage
07:29
009 Summary
04:29
04 – Dimensional Modeling
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001 What is dimensional modeling
03:26
002 Why dimensional modeling
04:34
003 Facts
05:03
004 Dimensions
04:26
005 Star schema
07:39
006 Snowflake schema
05:11
007 Demo Product & Category dimension (snowflaked)
10:18
05 – Facts
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001 Additivity
08:28
002 Nulls in facts
04:01
003 03-Year-to-Date-facts
03:19
003 Year-to-Date facts
03:19
004 Types of fact tables
00:32
005 Transactional fact tables
03:32
006 Periodic fact tables
03:51
007 Accumulating snapshots
03:34
008 Comparing fact table types
03:35
009 Factless fact tables
04:05
010 Steps in designing fact tables
04:40
011 Surrogate Keys
06:02
012 Case Study The Project
04:37
013 Case Study Identify the business process
02:05
014 Case Study Define the grain
02:59
015 Case Study Identify the dimensions
03:29
016 Case Study Identify the facts
05:25
06 – Dimensions
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001 Dimension tables
06:24
002 Date dimensions
07:24
003 Nulls in dimensions
04:42
004 Hierarchies in dimensions
04:47
005 Conformed dimensions
03:40
006 Degenerate dimensions
03:40
007 Junk dimension
08:07
008 Role-playing dimension
05:57
009 Case Study Date dimension
05:37
07 – Slowly Changing Dimensions
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001 What are slowly changing dimensions
03:14
002 Type 0 – Original
01:58
003 Type 1 – Overwrite
03:43
004 Type 2 – Additional row
05:27
005 Administrating Type 2 dimensions
05:55
006 Mixing Type 1 & Type 2
02:31
007 Type 3 – Additional attribute
06:00
08 – ETL process
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001 Understanding the ETL process
06:37
002 Extract
03:02
003 Initial Load
03:16
004 Delta Load
06:59
005 Load Workflow
04:15
006 Demo Quick Intro to Pentaho
09:32
007 Demo Setting up tables in SQL
04:58
008 Demo Initial Load example
10:05
009 Demo Delta Load example
13:38
010 Transforming data
04:37
011 Basic Transformations
06:05
012 Advanced Transformations
07:24
013 Demo Planning next steps
05:18
014 Demo Table setup & Complete Staging
09:11
015 Demo Transform
07:07
016 Demo Load & Validate results
05:45
017 Scheduling jobs
05:51
09 – ETL tools
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001 ETL tools
04:42
002 Choosing the right ETL tool
06:03
10 – Case Study Creating a Data Warehouse
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001 Plan of attack
02:23
002 Source data & table design
08:55
003 Setting up the tables in database
02:59
004 Staging Sales Fact
07:47
005 Staging job & fixing problems
06:34
006 Load Payment Dimension
05:34
007 Transform & Load Sales Fact
09:26
008 Transform & Load job
03:10
009 Final ETL job & Incremental Load
06:17
11 – ETL vs. ELT
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001 What is an ELT
05:15
002 ETL vs. ETL
04:54
12 – Using a Data Warehouse
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001 What are the common use cases
04:05
002 Connecting the DWH to Power BI
10:22
13 – Optimizing a Data Warehouse
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001 Using indexes
05:01
002 B-tree indexes
02:42
003 Bitmap indexes
03:31
004 Guidelines for indexes
07:41
005 Demo Setting indexes
03:56
14 – The Modern Data Warehouses
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001 Cloud vs. on-premise
02:47
002 Benefits cloud vs on-premise
05:50
003 Massive parallel processing
05:34
004 Columnar storage
04:19
Data Warehouse – The Ultimate Guide
Exercise Files
015 SQL-Transform.txt
Size: 399.00 B
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