Page 239 - Data Architecture

Chapter 6.3: Introduction to Data Vault Architecture

Fig. 6.3.1 Data Vault 2.0 architecture overview.

The sections are staging, EDW, and information marts or information delivery layer.
Regardless of platforms and technology utilized for implementation, these layers will
continue to exist. However, as the system nears full real-time enablement, the need and
dependency on the staging area will decline. True real-time data will feed directly into the

EDW layer.

In addition to the three tiers, the Data Vault 2.0 architecture dictates several different

components:

1. (a) The use of Hadoop or NoSQL to handle big data.
2. (b) The nature of real-time information flowing both IN and OUT of the business intelligence
ecosystem; in turn, this also evolves the EDW into an operational data warehouse over time.
3. (c) The use of managed self-service BI through write-back and master data capabilities enabling TQM
as well.
4. (d) Split of hard and soft business rules, making the enterprise data warehouse a system of record for
raw facts that are loaded over time.

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