Page 212 - Data Architecture

Chapter 6.1: Introduction to Data Vault 2.0
perform under large-volume load cycles. Furthermore, sequence numbering techniques
limit the team's ability to distribute the data vault model onto hybrid platforms (on-
premise/in-cloud) or onto geographically distributed platforms.

Enter: Data Vault 2.0

The New and Updated Data Vault 2.0

Since 2001, the technology, platforms, capabilities, and hardware have all changed and
shifted. Today's focus is on much larger big data systems, NoSQL platforms, and better
processing of unstructured/semistructured data. The methodology has been brought up to
date to include disciplined agile delivery (from Mark Lines and Scott Ambler). The
architecture includes landing zones, data lakes, and hybrid solution designs.

The data vault has evolved—just like the web, just like automobiles, or just like any
system. Data vault is now considered to be at a stable 2.0 release and includes (as

mentioned previously) model, methodology, implementation, and architecture. Data
Vault 2.0 (DV2) is a foundational system that provides programs and projects with the
knowledge and foresight to implement successful enterprise data warehouses.

The issues Data Vault 2.0 is built to solve include the following:

• Global distributed teams
• Global distributed physical data warehouse components
• “Lazy” joining during query time across multicountry servers
• Ingestion and query parsing of images, video, audio, and documents (unstructured data)
• Ingestion of real-time streaming (IOT) data
• Cloud and on-premise seamless integration
• Agile team delivery
• Incorporation of data virtualization and NoSQL platforms
• Extremely large data sets (into the petabyte ranges and beyond)
• Automation and generation of 80% of the work products

From a business perspective, DV2 brings the entire solution to the table—not only the
data model but also the workflow, processes, automation, standardization, adaptability,
architectural flexibility, agility, and more. From a business perspective, these components
can no longer be ignored. Cobbling together multiple different methodologies and hoping
for success rarely work.

DV2 brings tried and tested successes, empirical evidence that will not suffer the
consequences of reengineering. DV2 also brings confidence from customers, based on
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