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

Inf Sid, ETL/Data Architect

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39 Lessons (2h 45m)
    • 1. 01 - Is Data Warehouse still relevant in the age of Big Data

      4:25
    • 2. 02 - Why Data Warehouse is Implemented?

      4:51
    • 3. 03 - What is a Data Warehouse?

      5:48
    • 4. 04 - Chareterstics of a Data Warehouse

      5:43
    • 5. 05 - What is Business Intelligence?

      5:37
    • 6. 06 - What is Business Intelligence Part 2 Project Specific Set Up

      3:34
    • 7. 07 - Mutiple Uses of BI

      8:02
    • 8. 08 - Different Tools used in BI

      6:24
    • 9. 09 - Centrelized Data Warehouse Architectures

      4:46
    • 10. 10 - Federated Data Warehouse Architectures

      3:05
    • 11. 11 - Muitli Tired Data Warehouse Architectures

      3:13
    • 12. 12 - Components of Data Warehouse Architectures

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

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

      3:35
    • 15. 15 - Advantages of Data Warehouse

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

      6:01
    • 17. 17 - ODS - Operational Data Store

      2:20
    • 18. 19 - Features and Benefits of ODS

      2:18
    • 19. 18 - Define ODS

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

      4:01
    • 21. 21 - OLAP

      5:54
    • 22. 22 - OLAP Vs OLTP Part 1

      4:33
    • 23. 23 - OLAP Vs OLTP Part 2

      6:01
    • 24. 24 - MOLAP

      6:36
    • 25. 25 - ROLAP

      3:40
    • 26. 26 - HOLAP

      2:28
    • 27. 27 - DOLAP

      1:28
    • 28. 28 - DataMart

      1:47
    • 29. 28 - Fundamental Difference between DWH and DM

      0:36
    • 30. 29 - Advantages of a Data Mart

      2:40
    • 31. 30 - Charecteristics of a Data Mart

      4:00
    • 32. 31 - Disdvantages of a Data Mart

      3:13
    • 33. 32 - Mistakes and MisConceptions of a Data Mart

      2:15
    • 34. 33 - Metadata

      1:57
    • 35. 34 - Benefits of Metadata

      1:46
    • 36. 35 - Types of Metadata

      5:32
    • 37. 36 - Metadata Project Setup

      5:34
    • 38. 37 - Best Practices for Metadata Setup

      1:30
    • 39. 38 - Metadata Summary

      3:16

Project Description

This is a conceptual course to understand the Data Warehouse Concepts. There are mutiple case studies on different domains like Insurance, Retail, Banking, Telecom etc.

The pracctical case studies can be easily understood once all the parts of the Data Warehouse Concepts are clear.  

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