Layered or tiered architecture fortransformation of data from sources to utilisation. It includes three architectural columns that influence all layers

Processing activities for filtering, cleaning and transformation of datasets

Usage of the processed data in work processes in the consumer organisation

Analysing the cleaned, aggregated and filtered datasets

Selecting data sources on information content and data qualities

Data governance activities and application functions layers for maintaining qualities of the datasets

Application functions and activities for securing datasets and storage functionalities

Storage of primary and temporary datasets for usage in higher layers of the architecture

Not part of a data architecture but the input of the architecture, it is the raw material of a data pipe and therefore an essential part

Visualisation of the data or information for interpretation by analists and users