Master Data Warehouse Concepts - Step by Step from Scratch (Part 1) Premium class

Inf Sid, ETL/Data Architect

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39 Videos (2h 45m)
    • 01 - Is Data Warehouse still relevant in the age of Big Data

      4:25
    • 02 - Why Data Warehouse is Implemented?

      4:51
    • 03 - What is a Data Warehouse?

      5:48
    • 04 - Chareterstics of a Data Warehouse

      5:43
    • 05 - What is Business Intelligence?

      5:37
    • 06 - What is Business Intelligence Part 2 Project Specific Set Up

      3:34
    • 07 - Mutiple Uses of BI

      8:02
    • 08 - Different Tools used in BI

      6:24
    • 09 - Centrelized Data Warehouse Architectures

      4:46
    • 10 - Federated Data Warehouse Architectures

      3:05
    • 11 - Muitli Tired Data Warehouse Architectures

      3:13
    • 12 - Components of Data Warehouse Architectures

      3:57
    • 13 - Importance of Staging in Data Warehosue - Part 1

      4:43
    • 14 - Importance of Staging in Data Warehouse Part 2

      3:35
    • 15 - Advantages of Data Warehouse

      9:28
    • 16 - Disadvantages of a Traditional Data Warehouse

      6:01
    • 17 - ODS - Operational Data Store

      2:20
    • 19 - Features and Benefits of ODS

      2:18
    • 18 - Define ODS

      8:41
    • 20 - Differences Between OLTP, ODS and DWH

      4:01
    • 21 - OLAP

      5:54
    • 22 - OLAP Vs OLTP Part 1

      4:33
    • 23 - OLAP Vs OLTP Part 2

      6:01
    • 24 - MOLAP

      6:36
    • 25 - ROLAP

      3:40
    • 26 - HOLAP

      2:28
    • 27 - DOLAP

      1:28
    • 28 - DataMart

      1:47
    • 28 - Fundamental Difference between DWH and DM

      0:36
    • 29 - Advantages of a Data Mart

      2:40
    • 30 - Charecteristics of a Data Mart

      4:00
    • 31 - Disdvantages of a Data Mart

      3:13
    • 32 - Mistakes and MisConceptions of a Data Mart

      2:15
    • 33 - Metadata

      1:57
    • 34 - Benefits of Metadata

      1:46
    • 35 - Types of Metadata

      5:32
    • 36 - Metadata Project Setup

      5:34
    • 37 - Best Practices for Metadata Setup

      1:30
    • 38 - Metadata Summary

      3:16

About This Class

  • In this course, you would be learning all the concepts and terminologies related to the Datawarehouse , 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 !

88

Students

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Project

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.