Big Data Blueprint

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

Versie 1.0
Creatie datum 02-05-2021

Data processing

Processing activities for filtering, cleaning and transformation of datasets

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data processing

Data utilisation

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

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data utilisation

Data analysis

Analysing the cleaned, aggregated and filtered datasets

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data analysis

Data acquisition

Selecting data sources on information content and data qualities

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data acquisition

Data governance

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

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data governance

Data management

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data management

Data security

Application functions and activities for securing datasets and storage functionalities

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data security

Data storage

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

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data storage

Data sources

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

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data sources

Data visualisation

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

Auteur Bert Dingemans
Alias
Stereotypes ApplicationFunction
Details van Data visualisation