Data Vault: Building a Scalable Data Warehouse Kurzusok

Introduction

• The shortcomings of existing data warehouse data modeling architectures
• Benefits 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

How components interact with each other

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

Getting data into data entities

Loading Hub Entities

Loading Link Entities

Loading Satellites

Using SEI/CMM Level 5 templates to obtain repeatable, reliable, and quantifiable results

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

Building and deploying highly scalable and repeatable warehouses

Closing remarks