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      • Introduction to Data Modeling
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          • Introduction to Data Modeling
          • ETL
          • Fact Tables
          • Schema Types
          • Dimension Types
            • Conformed Dimension
            • Degenerated Dimension
            • Junk Dimension
            • Role Playing
            • Outrigger Dimension
            • Snowflake Dimension
            • Slowly Changing Dimension
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  • Apache Spark
    • Course Introduction
    • Python Vs. Scala
    • Introduction
    • About Databricks
    • Spark In The Data Platforms
    • Running Spark
    • Demo: Running Spark on Linux Ubuntu
    • Demo: Running Spark on MacOS
    • Demo: Running Spark on Windows
    • Demo Running Spark On Databricks
    • From Map Reduce To Spark
    • Spark Characteristics
    • Spark Applications
    • Spark Driver
    • Spark Session
    • Spark Cluster Manager
    • Spark Execution Mode
    • Spark Executors
    • Spark Data Partitioning
    • Spark Operations
    • Transformations Narrow Vs Wide
    • Demo: Immutability In Spark
    • Demo: RDD Text Manipulation
    • Demo: GroupByKey Vs. ReduceByKey
    • Demo: Joining RDDs
    • Demo: RDD Operations Part 1
    • Demo: Repartition Vs. Coalesce
  • Data Modeling
    • Introduction to Data Modeling
    • Fact Tables
    • Schema Types
    • Surrogate vs Natural Keys
    • Partitioning vs Bucketing
    • Kimball vs Inmon
    • Dimension Types
      • Conformed Dimension
      • Degenerated Dimension
      • Junk Dimension
      • Role Playing
      • Outrigger Dimension
      • Snowflake Dimension
      • Slowly Changing Dimension
      • Fast Changing Dimension
      • Shrunken Changing Dimension
      • Multi Valued Dimension
      • Swappable Dimension
      • Heterogeneous Dimension
  • Containerization
    • Short-lived containers
    • Long-lived containers
    • More than 1 container app
  • Big Data Engineering in Depth
    • Course Introduction
      • Introduction
      • Max Benefit
      • Assignments, Labs, & Textbooks
      • Course Content Overview
    • Data Warehouse
      • Introduction To Data Management
      • Data Abstraction
        • Introduction
        • Physical Layer
        • Logical Layer
        • View Layer
        • Data Solution Thinking
      • Data Warehouse Components
        • Motivation
        • DWH VS Transactional DB
        • Business Types
        • Use cases
        • Multi-temperature Storage
        • Characteristics & Components
        • Source System Integration Process
        • Source System Extraction
        • Staging Layer
        • Data Modeling
        • Introduction to Data Modeling
        • ETL
        • Fact Tables
        • Schema Types
        • Dimension Types
          • Conformed Dimension
          • Degenerated Dimension
          • Junk Dimension
          • Role Playing
          • Outrigger Dimension
          • Snowflake Dimension
          • Slowly Changing Dimension
          • Fast Changing Dimension
          • Shrunken Changing Dimension
          • Multi Valued Dimension
          • Swappable Dimension
          • Heterogeneous Dimension
  • Hadoop and Distributed Systems
    • Introduction To Distributed Systems
    • Hadoop
    • HDFS
    • YARN
    • Map Reduce
    • Hive
  • Still need help?
  • Join Discord ↗

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Courses
Data Modeling

Data Modeling in DWH

Topics

  1. Introduction to Data Modeling
  2. Dimension Types
    1. Conformed Dimension
    2. Degenerate Dimension
    3. Junk Dimension
    4. Role Playing Dimension
    5. Outrigger Dimension
    6. Snow Flake Dimension
    7. Slowly Changing Dimension
    8. Fast Changing Dimension
    9. Shrunken Rollup Dimension
    10. Multi Valued Dimension
    11. Swappable Dimension
    12. Heterogeneous Dimension
  3. Fact Tables
  4. Schema Types
  5. Surrogate Vs Natural Key
  6. Partitioning vs Bucketing
  7. Kimball vs Inmon
Last updated on Apr 19, 2020

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