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Course Outline

Introduction

  • Limitations of existing data warehouse modeling architectures
  • Advantages of Data Vault modeling

Overview of Data Vault architecture and design principles

  • SEI / CMM / Compliance

Data Vault applications

  • Dynamic Data Warehousing
  • Exploration Warehousing
  • In-Database Data Mining
  • Rapid Linking of External Information

Data Vault components

  • Hubs, Links, Satellites

Building a Data Vault

Modeling Hubs, Links, and Satellites

Data Vault reference rules

Interaction between components

Modeling and populating a Data Vault

Converting 3NF OLTP to a Data Vault Enterprise Data Warehouse (EDW)

Understanding load dates, end-dates, and join operations

Business keys, relationships, link tables, and join techniques

Query techniques

Load processing and query processing

Overview of Matrix Methodology

Ingesting data into data entities

Loading Hub Entities

Loading Link Entities

Loading Satellites

Utilizing SEI/CMM Level 5 templates to achieve repeatable, reliable, and quantifiable outcomes

Developing a consistent and repeatable ETL (Extract, Transform, Load) process

Building and deploying highly scalable and repeatable warehouses

Closing remarks

Requirements

  • A foundational understanding of data warehousing concepts
  • A foundational understanding of database and data modeling concepts

Target Audience

  • Data modelers
  • Data warehousing specialists
  • Business Intelligence specialists
  • Data engineers
  • Database administrators
 28 Hours

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