Traditional Data Architectures: Data Warehousing and ETL Systems

Data Architecture 2021
  • 12 Videos | 39m 31s
  • Includes Assessment
  • Earns a Badge
Data warehouses are actively used for business intelligence and, because they integrate data from multiple sources, are advantageous to simple databases in many instances. Considering modern companies often have ETL-based data warehousing systems, decision-makers need to comprehend how they operate and are appropriately managed. In this course, learn the necessary concepts and processes required to work with and manage projects related to data warehousing. Study data warehousing architectures and schemas and investigate some core data warehouse elements, such as dimension, fact tables, and keys. Furthermore, examine the extract, transform, and load (ETL) approach for working with data warehouses, specifying process flow, tools, and software as well as best practices. When you're done, you'll know how to adopt data warehousing and ETL systems for your business intelligence and data management needs.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe how a data warehouse is different from a database and how data warehouses are used for business intelligence
    name and define three main tiers of a data warehouse
    compare and contrast various data warehousing schemas, such as Star, Snowflake, etc.
    name use cases of dimension tables and define different types of dimensions and their granularity
    define fact table measures, describe how measures are added and loaded, and outline the steps for implementing a fact table in a data warehouse
  • describe how data warehouse keys work, specifying the importance of surrogate keys
    describe extract, transform, and load (ETL) functionality and specify how the movement between transactional OLTP databases and a data warehouse is performed and how to organize and design your extraction, transformation, and loading capabilities to keep your data warehouse up-to-date
    describe the ETL framework and it's three main components - extraction, transformation, and loading
    name and describe the most commonly used ETL tools and software
    specify best practices to be followed when dealing with ETL to perform operations as efficiently as possible
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 38s
    UP NEXT
  • Playable
    2. 
    Data Warehousing for Business Intelligence
    3m 56s
  • Locked
    3. 
    Data Warehouse Architecture
    3m 58s
  • Locked
    4. 
    Data Warehousing Schemas
    3m 58s
  • Locked
    5. 
    Dimension Table Use Cases
    3m 14s
  • Locked
    6. 
    Fact Tables in a Data Warehouse
    3m 18s
  • Locked
    7. 
    Keys in Data Warehouse Schemas
    3m 31s
  • Locked
    8. 
    What Is ETL?
    2m 59s
  • Locked
    9. 
    What Is ETL, ETL Framework, and Process Flow?
    5m 14s
  • Locked
    10. 
    Extract, Transform, and Load (ETL) Tools
    3m 14s
  • Locked
    11. 
    Extract, Transform, and Load (ETL) Best Practices
    3m 24s
  • Locked
    12. 
    Course Summary
    1m 6s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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