Data Warehouse (DWH) | COURSE PLEASE

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  1. 1 | Why Data Warehouse Need? 00:04:42
  2. 2 | What Is Data Warehouse? 00:04:20
  3. 3 | Power of Business Intelligence in Data Warehouses 00:02:47
  4. 4 | Data Warehouse vs Data Lake 00:06:24
  5. 5 | SetUp Pentaho ETL Tool & PostgreSQL Database 00:10:31
  6. 6 | Unraveling the Layers of Data Warehouse: A Staging Layer Demonstration 00:17:26
  7. 7 | Data MARTS: Unlocking Insights for Better Decision-Making 00:06:27
  8. 8 | Database Relations in Data Warehouses 00:06:24
  9. 9 | OLAP Cubes: Unleashing Multi-Dimensional Data Insights 00:07:48
  10. 10 | Operational Data Storage: Managing Real-Time Data for Seamless Operations 00:07:29
  11. 11 | Dimensional Modeling Explained: Unraveling the Power of Simplified Data Analysis 00:08:00
  12. 12 | Facts in Data Warehousing: The Backbone of Actionable Insights 00:05:04
  13. 13 | Dimensions in Data Warehousing: Navigating the Pathways of Data Understanding 00:04:26
  14. 14 | Star Schema vs. Snowflake Schema: Unraveling the Best Data Modeling Practices 00:23:08
  15. 15 | Additivity, Nulls, and Year-to-Date: Exploring Key Concepts in Fact 00:15:48
  16. 16 | Step-by-Step Guide: Creating a Fact Table for Data Warehousing 00:04:40
  17. 17 | Fact Types: Transactional, Periodic, Accumulate Snapshot, and Factless - A Comprehensive Comparison" 00:19:09
  18. 18 | Natural vs. Surrogate Keys: Making Informed Choices for Database Design 00:06:03
  19. 19 | Case study project of Fact in data warehouse 00:18:35
  20. 20 | Dimensions in Data Warehousing:Tables, Date Null & Dimensions 00:18:30
  21. 21 | Demystifying Dimension Types: Hierarchical, Conformed, Role-Play, Degenerate, and Junk Dimensions 00:28:15
  22. 22 | Dimensional Modeling Case Study: Unraveling Effective Data Organization and Analysis 00:05:38
  23. 23 | Slowly Changing Dimensions: Preserving Data History in Data Warehousing 00:03:15
  24. 24 | Understanding Dimensional Changes: Exploring Type 0, Type 1, and Type 2 Slowly Changing Dimensions" 00:11:08
  25. 25 | Administering Mixed Type 1 and Type 2 Dimensions: Navigating Type 2 Dimensions with Added Attributes 00:14:26
  26. 26 | ETL Process: Streamlining Data Warehouse Operations 00:12:55
  27. 27 | ETL Processes: Delta Load, Load Strategies, and Pentaho Data Integration 00:20:46
  28. 28 | ETL process : Setting Up Tables, Initial Data, and Delta Loads with Live Examples! 00:28:41
  29. 29 | ETL - Mastering Data Transformation: Basic to Advanced Techniques Explained 00:23:24
  30. 30 | ETL process : Setup, Staging, Transformation, Loading, Validation, and Job Scheduling Demos 00:27:54
  31. 31 | ETL Tools 00:10:45
  32. 32 | Mastering Data Warehouse: Strategic Planning, Table Design, and Staging Success 00:28:38
  33. 33 | Mastering ETL : Transforming Payments, Sales, and Jobs in Your Data Warehouse 00:24:27
  34. 34 | ETL vs ELT: Unraveling the Data Integration Debate 00:10:09
  35. 35 | Unlocking Strategic Insights: The Power and Promise of Data Warehousing #usecases #datawarehouse 00:14:27
  36. 36 | Indexing Techniques in Data Warehousing: B-Tree, Bitmap 00:11:14
  37. 37 | Mastering Index Guidelines for Fact & Dimension Tables Practical Demo #datawarehouse #indexing 00:11:37
  38. 38 | Cloud vs On-Premises, Massive Parallel Processing(MPP) ,Columnar Database #datawarehouse 00:18:30
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    Youtube

    29-07-2024
    Data Warehouse Zero To Master

    Welcome to "The Ultimate Data Warehouse Playlist," your go-to resource for mastering the art of data analytics and unleashing the full potential of your data. Whether you're a beginner or an experienced data professional, this curated collection of videos will guide you through the intricacies of building, optimizing, and utilizing data warehouses effectively.
    In this playlist, we've carefully selected a series of insightful videos from industry experts, thought leaders, and seasoned practitioners. Each video offers valuable insights, practical tips, and best practices to help you navigate the complex world of data warehousing and extract meaningful insights from your data.