The data machine concept describes three major technological functionalities that are
often vital to technological environment operations. This architectural concept tackles major data
operation imperatives that an underlying technology must address. (Exhibit 15.19 illustrates the
capabilities of these major architectural concepts.)
??? Aggregation and manipulation. This is simply the process by which data, content, or
information is collected from various sources, such as databases, meta-data repositories,
policy repositories, or even from third-party content providers. An aggregation operation
also combines and prepares data for future transactions, reporting activities, retrieval by
various services, and even archiving. These activities are typically offered by third-party
vendor middleware products that perform collection duties and manipulate the aggregated
content by matching, combining, enriching, and concatenating it for future use. In addition,
the aggregation process can also offer data validation, integrity, and cleansing, so
that unwanted information is stripped out without harming the data??™s completeness.
328 Ch. 15 Service-Oriented Conceptual Architecture Modeling Principles
Data
Retrieval and
Storage
Data Machine
Data
Aggregation
Data
Cleansing
Data
Enriching
Data
Validation
Data
Searching
EXHIBIT 15.19 CONCEPTUAL DATA MACHINE CAPABILITIES
The service-oriented paradigm offers two major data aggregation models that are currently
used for collecting and processing data in interoperable environments, across lines
of business, and business domains: (1) The transactional central hub model enables collection
of data that is distributed across multiple organizations.
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