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Enterprise Data WareHouse (EDWH)

This is the logical application of a data warehouse not the component. It describes the functionality of storing, modeling updating and retrieving enterprise data based on relational data including the history of the data

Package BD-DWH Integration ABB
Author 102401
Alias --
Stereotypes ApplicationFunction

Diagrams

Serial BDP-DWH ABB

Serial integration is implemented by introducing a big data platform for the transformation and extraction of unstructured and semi structured data as source for the EDWH functionality. Characteristics
  • Introduction of the big data platform is relatively easy since it is an extra layer added to the DWH functionality
  • Relative easy big data patterns are available because the source is always the datawarehouse
  • Introducing big data solutions for other functionalities than DHW is not possible.

Parallel BDP-DWH ABB

The parallel integration is an extension of the DWH functiionality with the Big Data Platform. This extension makes it possible to use both functionalities side by side. Characteristics
  • Easy (incremental) introduction of the Big Data functionality
  • Integration of both functionalities requires attention for the introduction of the interconnect functionality because this can become a bottleneck in performance and configuration

Appliance BDP-DWH ABB

In the appliance integration of a big data platform with DWH functionality the appliance acts like a black box in which all functionality is integrated in a (proprietary) solution. This solution is configured for optimal performance of transformation and analysis. Characteristics
  • Appliance is developed, configured and often maintained by an external supplier
  • It is introduced as a fully integrated solution therefore existing implementations of the DWH have to migrate to this solution
  • Appliances are often introduced when a cloud solution is selected for the data platform

Virtualisation BDP-DWH ABB

This integration pattern has a close relation with the parallel integration, however there is an extra layer introduced for the virtualisation and standardisation of data extraction to consumers of the data. Characteristics
  • Virtualisation layer encapsulate the internal confuguration of the two platforms
  • The virtualisation layer requires a standardized data or objectmodel for the extraction by the consumers
  • The virtualisation can become a bottleneck in a number of qualities like performance, integratability e.g.

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