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Business Analytics & Intelligence
Data Warehouse
Data Warehouse Concepts: Basic to Advanced concepts

Data Warehouse Concepts: Basic to Advanced concepts

Loại khoá học: Business Analytics & Intelligence

Data Warehouse Concepts: Learn the in BI/Data Warehouse/BIG DATA Concepts from scratch and become an expert.

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50.000 VND
1.349.000 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

In this course, you will learn all the concepts and terminologies related to the Data Warehouse , such as the OLTP, OLAP, Dimensions, Facts and much more, along with other concepts related to it such as what is meant by Start Schema, Snow flake Schema, other options available and their differences. It also explains how the data is managed with in the Data Warehouse and explains the process of reading and writing data onto the Warehouse. Later in the course you would also learn the basics of Data Modelling and how to start with it logically and physically. You would also learn all the concepts related to Facts, Dimensions, Aggregations and commonly used techniques of ETL. Upon completion of this course, you would have a clear idea about, all the concepts related to the Data Warehouse, that should be sufficient to help you start off with the next step of becoming an ETL developer or Administering the Data warehouse environment with the help of various tools. All the Best and Happy Learning !

Bạn sẽ học được gì

Learning all the concepts and terminologies related to the Datawarehouse , such as the OLTP, OLAP, Dimensions, Facts, Start Schema, Snow flake Schema etc

It also explains how the data is managed with in the Data Warehouse and explains the process of reading and writing data onto the Warehouse.

Later in the course you would also learn the basics of Data Modelling and how to start with it logically and physically.

You would also learn all the concepts related to Facts, Dimensions, Aggregations and commonly used techniques of ETL.

Yêu cầu

  • Basic understanding of the IT (Software) industry
  • Familiar with the basic concept of Database/RDBMS.

Nội dung khoá học

18 sections

Introduction

1 lectures
Welcome! Thank you for learning the Data Warehouse concepts with me!
06:20

Brief about the Data warehouse

4 lectures
Is Data Warehouse still relevant in the age of Big Data?
04:25
Why do we need a Data Warehouse?
05:26
What is a Data Warehouse?
05:42
Characteristics of a Data Warehouse
05:40

Business Intelligence

4 lectures
What is Business Intelligence?
05:37
Business Intelligence -Extended Explanation
03:34
Uses of Business Intelligence
08:02
Tools used for (in) Business Intelligence
06:24

Data Warehouse Architectures

8 lectures
Enterprise Architecture or Centralized Architecture
04:46
Federated Architecture
03:05
Multi-Tired Architecture
03:13
Components of a Data Warehouse
03:57
Purpose of a Staging Area in Data Warehouse Architecture - Part 1
04:49
Purpose of a Staging Area in Data Warehouse Architecture - Part 2
03:41
Advantages of Traditional warehouse
02:33
Limitations of Traditional Data Warehouses
06:08

ODS - Operational Data Store

4 lectures
What is ODS?
02:26
Define ODS
07:40
Staging Vs ODS
01:56
Differences between ODS,DWH, OLTP, OLAP, DSS
04:07

OLAP

7 lectures
OLAP Overview
05:17
OLTP Vs OLAP - Part 1_U
04:05
OLTP Vs OLAP - Part 2
05:31
OLAP Architecture - MOLAP
05:56
ROLAP
03:35
HOLAP
02:20
DOLAP
01:31

Data Mart

6 lectures
What is a Data Mart?
01:40
Fundamental Difference between DWH and DM
00:40
Advantages of a Data Mart
02:46
Characteristics of a Data Mart
03:37
Disadvantages of a Data Mart
03:01
Mistakes and MisConceptions of a Data Mart
02:08

Metadata

6 lectures
Overview of Metadata
01:50
Benefits of Metadata
01:47
Types of Metadata
05:38
Projects on Metadata
05:28
Best Practices for Metadata Setup
01:36
Summary
03:11

Data Modeling

2 lectures
What is Data Modeling?
02:11
Data Modeling Techniques
03:42

Entity Relational Data Model

14 lectures
ER - (Entity Relation) Data Model
03:37
ER Data Model - What is Entity?
02:01
ER Data Model - Types of Entities - Part 1
03:57
ER Data Model - Types of Entities - Part 2
01:49
ER Data Model - Attributes
01:54
ER Data Model - Types of Attributes
03:59
ER Data Model - Entity-Set and Keys
02:42
ER Data Model - Identifier
01:53
ER Data Model - Relationship
01:15
ER Data Model - Notation
02:34
ER Data Model - Logical Data Model
01:30
ER Data Model - Moving from Logical Data Model to Physical Data Model
02:14
ER Data Model - Differences between CDM, LDM and PDM
03:06
ER Data Model - Disadvantages
03:15

Dimensional Model

21 lectures
What is Dimension Modelling?
04:38
Benefits of Dimensional Modelling
01:52
What is a Dimension?
02:36
What is a Fact?
02:00
Additive Facts
01:45
Semi Additive Facts
02:23
Non-Additive Facts
01:26
FactLess Facts
02:26
What is a Surrogate key?
03:45
Star Schema
04:54
SnowFlake Schema
03:22
Galaxy Schema or Fact Constellation Schema
02:25
Differences between Star Schema and SnowFlake Schema?
04:55
Conformed Dimension
06:17
Junk Dimension
03:12
Degenerate Dimension
03:36
Slowly Changing Dimensions - Intro and Example Creation
05:35
Slowly Changing Dimensions - Type 1, 2 and 3
12:14
Slowly Changing Dimensions - Summary
03:05
Step by Step approach to set up the Dimensional Model using a retail case study
06:44
ER Model Vs Dimensional Model
05:22

DWH Indexes

4 lectures
What is an Index?
02:04
Bitmap Index
03:46
B-Tree index
01:49
Bitmap Index Vs B Tree Index
03:20

Data Integration and ETL

3 lectures
What is Data Integration?
06:49
What is ETL?
03:49
Common Questions and Summary
02:42

ETL Vs ELT

3 lectures
ETL - Explained
06:03
ELT - Explained
05:24
ETL Vs ELT
02:18

ETL - Extraction Transformation & Loading

3 lectures
Build Vs Buy
05:10
ETL Tools for Data Warehouses
01:56
Extraction Methods in Data Warehouses
05:42

Typical Roles In DWH Project

13 lectures
Project Sponsor
03:24
Project Manager
01:46
Functional Analyst or Business Analyst
02:53
SME - Subject Matter Expert
04:17
DW BI Architect
03:07
Data Modeler
08:59
DWH Tech Admin
01:20
ETL Developers
01:56
BI OLAP Developers
01:29
ETL Testers/QA Group
01:58
DB UNIX Network Admins
00:56
Data Architect, Data Warehouse Architect, BI Architect and Solution Architect
09:57
Final Note about the Roles
02:16

DW/BI/ETL Implementation Approach

18 lectures
Different phases in DW/BI/ETL Implementation Approach
01:51
Knowledge Capture Sessions
03:34
Requirements
07:21
Architecture phases
04:48
Data Model/Database
01:35
ETL Phase
02:43
Data Access Phase
02:10
Data Access Types - Selection
01:37
Data Access Types - Drilling Down
00:58
Data Access Types - Exception Reporting
00:36
Data Access Types - Calculations
01:26
Data Access Types - Graphics and Visualization
00:58
Data Access Types -Data Entry Options
02:04
Data Access Types - Customization
01:00
Data Access Types - WebBased Reporting
00:56
Data Access Types - BroadCasting
01:04
Deploy
01:42
Iterative Approach
03:25

Retired Lectures

1 lectures
ETL Vs ELT
02:23

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