What is the process model perspective for the Data Warehouse, and how does it differ from the data model perspective?

  • Process model

In the process model perspective of the data warehouse the way of producing known outputs from known inputs is the focus, i.e. the whole-life process and metadata is attached throughout the life of the data item. The focal point is not the data itself but the processes defined to generate multiple outputs from one input or use multiple contributions to a single output. The data acquisition is driven by the types of outputs to be produced, and vice versa. Naturally, changes in inputs or outputs affect the processes. In this perspective, the data warehouse supports the set of production processes needed to manage the inputs and generate the outputs.






  • Data model

In the data model perspective the core is a unit for storing data, irrespective of where it has come from or where it is going to and the process is not designed around either the input or output, but focusing on the data item. Data acquisition is driven by availability of sources while the output production is driven by the accessibility of data stored in the data warehouse. Getting the data from a source and converting it to an usable form is a separate part. Similarly, producing a type of output is a discrete process. Changes in the input processes do not affect output processes and vice versa.