Master Data Warehouse Concepts - Step by Step from Scratch (Part 2) - Dimensional Modeling Premium class

Inf Sid, ETL/Data Architect

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37 Videos (2h 22m)
    • Data Modelling Introduction

      2:13
    • Data Modelling Techniques

      3:53
    • Entity Relationship (ER) Data Model

      3:41
    • ER Modelling Logical Design

      15:30
    • ER Modelling Logical Design Entity

      1:59
    • ER Modelling Logical Design Types of Entities 1

      4:01
    • ER Modelling Logical Design Types of Entities 2

      2:09
    • ER Modelling Logical Design Attributes

      1:54
    • ER Modelling Logical Design Identifier

      2:02
    • ER Modelling Logical Design Notation

      2:37
    • ER Modelling Logical Design RelationShip

      1:15
    • ER Modelling Logical Design Logical Data Model

      1:29
    • LDM to PDM

      2:26
    • Physical Design

      4:02
    • Differences between CDM, LDM PDM

      3:30
    • Disadvantages of ER Model

      3:33
    • Dimensional Modeling - Introduction

      4:39
    • Dimensional Modeling - Benefits

      1:50
    • Dimensions Explained

      2:48
    • Facts Explained

      2:05
    • Additive Facts

      1:45
    • Semi Additive

      2:28
    • Non Additive Facts

      1:30
    • FactLess Facts

      2:29
    • Surrogate Keys

      4:01
    • Star Schema

      5:23
    • SnowFlake Schema

      3:25
    • Galaxy Schema

      2:20
    • Differences between Star and SnowFlake

      5:27
    • Conformed Dimensions

      6:38
    • Junk Dimension

      3:06
    • Degenerate Dimension

      3:35
    • SCD - Slowly Changing Dimensions

      5:30
    • SCD Type 1 2 3

      12:30
    • SCD Summary

      3:33
    • Step by Step Approach of creating a Dimensional Model

      7:28
    • Differences between ER and Dimensional Modeling For DWH

      5:50

About This Class

This is part of the Master Data Warehouse Concepts - Step by Step from Scratch (Part 1)

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 !

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Inf Sid

ETL/Data Architect

Business Intelligence Consultant and Trainer with 13+ 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.