The DCA Symposium is a great way to find out why & how to pragmatically change from an application-centric paradigm to a data centric one! Too often, our approach to systems functionality is to reach for the next application or integration instead of looking what additional value can be extracted from data within the enterprise…
No knowledge, no AI? If you want meaningful results from an AI or ML project, then make sure your data house is in order – data, metadata, content & their curation – otherwise you are just fuelling your systems with your past mistakes. Of course, it may be an expensive way of doing it, but…
Actively using metadata is both a smart way to help de-risk your domain and inevitable for a rewarding digital future based on knowledge infrastructure, the corporate nervous system. How aware is your business of metadata, and how it can presage both risk & reward? The regulatory environment spans personally identifiable information (PII), consumer data (GDPR,…
Semantics is the logic of meaning and how referential relationships inform that. Concepts using natural language are the basis of the semantic model, an ontology which sets out this logic and ensures consistency of meaning. Semantic tags reflect imaginative human concepts & vocabulary, not the linear machine terminology of applications. They should reflect how the…
As Steve Miller, formerly at Gresham Tech pointed out: “One fundamental barrier is that most banks and large enterprises rely on architectures that have evolved over time. In fact, ‘architecture’ may not even be the right term, as that implies a level of intent and design that can often be wholly absent. In a sense these…
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. This is such a complex environment that visual presentation is essential.…
Given that data sources may include the following, the chances of your migration (to cloud) working first time round, are very small: Each cloud has its own characteristics and may be informed by: Different data sources require different discovery and preparation: If the source data is in a packaged application, this does not necessarily guarantee…
Data validation tests the accuracy, consistency (of format and standards), quality and integrity of the data (& associated metadata) for onward information engineering, data provisioning and curation. Note that ‘reliable’ data still needs to be validated. Even though this is not its primary purpose, data anomalies revealed by validation techniques can reveal hitherto unnoticed business…
The term ‘ontology’ (which can be off-putting) is understood as ‘the study of being’ or the ‘logic of existence’. In this context, it applies to content – why does this content exist? The ontology acts as the organising mind: a generalisable framework for understanding entities, their context & relationships, using semantic tags. It is an…