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Application Integration::Population=Multi Step Process variation::Runtime patterns

Population=Multi Step Process variation::Runtime patterns

Population=Multi Step Process variation::Runtime pattern Data Server Services Data Server Services Population Population Population Population
Design Last Updated: 10-20-2004
(Click a node to get a detailed explanation.)

The figure above shows the Runtime pattern for this Multi Step Process variation for cleansing of structured data.

The main pathway in this Multi Step Process variation is through the Population nodes from the source on the right to the target on the left, cleansing data through a complex Processing stage on its way, for example, from an operational system to the data warehouse. However, an additional pathway is provided to apply the corrections to the data back to the source in order to avoid cleansing the same data again on subsequent runs. An alternative approach is to write the cleansed data only back to the source and to use a standard Population pattern to later update the target data store.

For examples of runtimes for unstructured data, please refer to the redbook Patterns: Portal Search Custom Design, SG24-6881.

Next, review product mappings for this Runtime design.

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Data Server/Services

A Data Server/Services node is a generic data storage node that provides managed, persistent storage of any type of data and a means to directly access and manipulate that data. The data may be stored in files and accessed through file I/O routines or may be stored in a database with more structured and managed access methods.

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Population

A population node is a specialized application or data server that is optimized for record-oriented processing where the records must be gathered from one or more source data sets, processed singly and multiply and finally applied to one or more target data sets. A population node typically operates in an "off-line" mode to prepare data in advance of its business usage and based on rules that have been previously defined through a separate user interface module and stored in a metadata repository.

A population server may be further specialized for one or two of its inherent sub-functions--gather, process or apply (also known as extract, transform and load respectively). Such specialization may be for reasons of performance or physical placement.