Data Warehouse Concepts: Basic to Advanced concepts
Data Warehouse Concepts: Learn the in BI/Data Warehouse/BIG DATA Concepts from scratch and become an expert.
Created by Inf Sid, Last Updated 23-Oct-2019, Language:English
Description
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 !
Requirements
- Basic understanding of the IT (Software) industry
- Familiar with the basic concept of Database/RDBMS.
What Will I Get ?
- Brief about the Data Warehouse and how the concept came into existence
- Business Intelligence Concepts
- Data Warehouse Architectures
- ODS - Operational Data Store
- OLAP - Online Analytical Processing
- Data Marts
- Metadata
- Data Modeling
- Entity Relationship Model
- Dimensional Model
- Data Integration & ETL
- ETL vs ELT
- ETL - Extraction Transformation & Loading
- Typical Roles in a Data Warehouse Project
- DW/BI/ETL Implementation Approach
Course Content
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Brief about the Data warehouse
4 Lectures
00:21:22
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Business Intelligence
4 Lectures
00:23:37
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What is Business Intelligence?
00:05:37 -
Business Intelligence -Extended Explanation
00:03:34 -
Uses of Business Intelligence
00:08:02 -
Tools used for (in) Business Intelligence
00:06:24
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Data Warehouse Architectures
8 Lectures
00:31:18
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Enterprise Architecture or Centralized Architecture
00:04:08 -
Federated Architecture
00:02:49 -
Multi-Tired Architecture
00:03:13 -
Components of a Data Warehouse
00:03:57 -
Purpose of a Staging Area in Data Warehouse Architecture - Part 1
00:04:49 -
Purpose of a Staging Area in Data Warehouse Architecture - Part 2
00:03:41 -
Advantages of Traditional warehouse
00:02:33 -
Limitations of Traditional Data Warehouses
00:06:08
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ODS - Operational Data Store
4 Lectures
00:16:37
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What is ODS?
00:02:26 -
Define ODS
00:07:40 -
Features and Benefits of ODS
00:02:24 -
Differences between ODS,DWH, OLTP, OLAP, DSS
00:04:07
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OLAP
7 Lectures
00:28:51
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OLAP Overview
00:05:54 -
OLTP Vs OLAP - Part 1
00:04:05 -
OLTP Vs OLAP - Part 2
00:05:31 -
OLAP Architecture - MOLAP
00:05:56 -
ROLAP
00:03:35 -
HOLAP
00:02:20 -
DOLAP
00:01:30
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Data Mart
6 Lectures
00:13:52
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What is a Data Mart?
00:01:40 -
Fundamental Difference between DWH and DM
00:00:40 -
Advantages of a Data Mart
00:02:46 -
Characteristics of a Data Mart
00:03:37 -
Disadvantages of a Data Mart
00:03:01 -
Mistakes and MisConceptions of a Data Mart
00:02:08
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Metadata
6 Lectures
00:19:30
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Overview of Metadata
00:01:50 -
Benefits of Metadata
00:01:47 -
Types of Metadata
00:05:38 -
Projects on Metadata
00:05:28 -
Best Practices for Metadata Setup
00:01:36 -
Summary
00:03:11
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Data Modeling
2 Lectures
00:05:53
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What is Data Modeling?
00:02:11 -
Data Modeling Techniques
00:03:42
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Entity Relational Data Model
14 Lectures
00:35:45
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ER - (Entity Relation) Data Model
00:03:37 -
ER Data Model - What is Entity?
00:02:01 -
ER Data Model - Types of Entities - Part 1
00:03:56 -
ER Data Model - Types of Entities - Part 2
00:01:49 -
ER Data Model - Attributes
00:01:54 -
ER Data Model - Types of Attributes
00:03:59 -
ER Data Model - Entity-Set and Keys
00:02:42 -
ER Data Model - Identifier
00:01:53 -
ER Data Model - Relationship
00:01:15 -
ER Data Model - Notation
00:02:34 -
ER Data Model - Logical Data Model
00:01:30 -
ER Data Model - Moving from Logical Data Model to Physical Data Model
00:02:14 -
ER Data Model - Differences between CDM, LDM and PDM
00:03:06 -
ER Data Model - Disadvantages
00:03:15
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Dimensional Model
21 Lectures
01:24:27
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What is Dimension Modelling?
00:04:38 -
Benefits of Dimensional Modelling
00:01:52 -
What is a Dimension?
00:02:36 -
What is a Fact?
00:02:00 -
Additive Facts
00:01:45 -
Semi Additive Facts
00:02:23 -
Non-Additive Facts
00:01:26 -
FactLess Facts
00:02:26 -
What is a Surrogate key?
00:03:45 -
Star Schema
00:04:54 -
SnowFlake Schema
00:03:22 -
Galaxy Schema or Fact Constellation Schema
00:02:20 -
Differences between Star Schema and SnowFlake Schema?
00:04:55 -
Conformed Dimension
00:06:17 -
Junk Dimension
00:03:12 -
Degenerate Dimension
00:03:36 -
Slowly Changing Dimensions - Intro and Example Creation
00:05:35 -
Slowly Changing Dimensions - Type 1, 2 and 3
00:12:14 -
Slowly Changing Dimensions - Summary
00:03:05 -
Step by Step approach to set up the Dimensional Model using a retail case study
00:06:44 -
ER Model Vs Dimensional Model
00:05:22
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DWH Indexes
4 Lectures
00:10:59
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What is an Index?
00:02:04 -
Bitmap Index
00:03:46 -
B-Tree index
00:01:49 -
Bitmap Index Vs B Tree Index
00:03:20
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Data Integration and ETL
3 Lectures
00:13:20
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What is Data Integration?
00:06:49 -
What is ETL?
00:03:49 -
Common Questions and Summary
00:02:42
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ETL Vs ELT
3 Lectures
00:13:45
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ETL - Explained
00:06:03 -
ELT - Explained
00:05:24 -
ETL Vs ELT
00:02:18
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ETL - Extraction Transformation & Loading
3 Lectures
00:12:48
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Build Vs Buy
00:05:10 -
ETL Tools for Data Warehouses
00:01:56 -
Extraction Methods in Data Warehouses
00:05:42
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Typical Roles In DWH Project
13 Lectures
00:44:18
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Project Sponsor
00:03:24 -
Project Manager
00:01:46 -
Functional Analyst or Business Analyst
00:02:53 -
SME - Subject Matter Expert
00:04:17 -
DW BI Architect
00:03:07 -
Data Modeler
00:08:59 -
DWH Tech Admin
00:01:20 -
ETL Developers
00:01:56 -
BI OLAP Developers
00:01:29 -
ETL Testers/QA Group
00:01:58 -
DB UNIX Network Admins
00:00:56 -
Data Architect, Data Warehouse Architect, BI Architect and Solution Architect
00:09:57 -
Final Note about the Roles
00:02:16
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DW/BI/ETL Implementation Approach
18 Lectures
00:39:48
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Different phases in DW/BI/ETL Implementation Approach
00:01:51 -
Knowledge Capture Sessions
00:03:34 -
Requirements
00:07:21 -
Architecture phases
00:04:48 -
Data Model/Database
00:01:35 -
ETL Phase
00:02:43 -
Data Access Phase
00:02:10 -
Data Access Types - Selection
00:01:37 -
Data Access Types - Drilling Down
00:00:58 -
Data Access Types - Exception Reporting
00:00:36 -
Data Access Types - Calculations
00:01:26 -
Data Access Types - Graphics and Visualization
00:00:58 -
Data Access Types -Data Entry Options
00:02:04 -
Data Access Types - Customization
00:01:00 -
Data Access Types - WebBased Reporting
00:00:56 -
Data Access Types - BroadCasting
00:01:04 -
Deploy
00:01:42 -
Iterative Approach
00:03:25
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Inf Sid
Data Management Consultant
Business Intelligence Consultant and Trainer with 16+ years of extensive work experience on various client engagements. Delivered many large data warehousing projects and trained numerous professionals on business intelligence technologies. Extensively worked on all facets of data warehousing including requirement gathering, gap analysis, database design, data integration, data modeling, enterprise reporting, data analytics, data quality, data visualization, OLAP. Has worked on broad range of business verticals and hold exceptional expertise on various ETL tools like Informatica Powercenter, SSIS, ODI and IDQ, Data Virtualization, DVO, MDM.
