The meaningful model

Modelling techniques are vital in digital, where the distinction between logical and physical dataflows has been overtaken by the need to ensure the business has the data to deliver on its intentions – from the centre to the edge and all points in between.

Ontology, moi?

This is such a complex environment that visual presentation is essential. The bigger the data volumes grow; the bigger the digital footprint; the more necessary it is to always have ‘kiss’ (‘keep it simple, stupid) in mind. So modelling now has to take into account not only multi-dimensionality but also semantic consistency – the model (even in early stages) has to have ontological integrity so that the business will be able to turn data, into information, into knowledge.

Modelling meaning?

If your data does not have meaning and consistency, what then the chances the model is relevant? Increasingly, data techniques and tools need to look to the long term digital strategy, to knowledge, not just be satisfied with immediate, tactical fixes.