Page 210 - Data Architecture

Chapter 6.1: Introduction to Data Vault 2.0
Chapter 6.1

Introduction to Data Vault 2.0

Abstract

One of the most important components of the end-state architecture is that of the data
vault. The data vault exists to satisfy the need for rock-solid data integrity. Like all other
components of the end-state architecture, the data vault has gone through its own
evolution. And like all components of the end-state architecture, data vault will continue

to evolve.

Keywords

Big data; Data vault; Lockheed Martin; NoSQL; Link; Hub; Satellite

“Data Vault 2.0” is a system of business intelligence that includes modeling,
methodology, architecture, and implementation best practices. The components also

known as pillars of Data Vault 2.0 are identified as follows:

• Data Vault 2.0 modeling—focused on process and data models
• Data Vault 2.0 methodology—following Scrum and agile ways of working
• Data Vault 2.0 architecture—includes NoSQL and big data systems
• Data Vault 2.0 implementation—pattern-based automation and generation

The term “data vault” is merely a marketing term chosen in 2001 to represent the system
to the market. The true name for the data vault system of business intelligence (BI) is
common foundational warehouse modeling, methodology, architecture, and
implementation.

The system includes aspects relating to the business of designing, implementing, and
managing an enterprise data warehouse. With the Data Vault 2.0 (DV2) system, the
organization can build incrementally, distributed or centralized, in the cloud or on-

premise with disciplined agile teams.

Each of these components plays a key role in the overall success of an enterprise data

warehousing program. These components are combined with industry-accepted practices
rooted in Capability Maturity Model Integration (CMMI), Six Sigma, total quality

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