Unless you are a librarian or archivist, metadata in the context of archives will probably have received scant attention. When organisations consign content, data & its metadata to storage oblivion, they tend to forget those archives also include metadata (in varying degrees of health). Metadata is also data. It can be more valuable than the…
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…
Why you need our knowledge strategy workshop Most organisations possess 80% unstructured content, most of which is under-utilised because it is not understood; is too big to easily or effectively search; is split amongst applications causing downstream integration costs; is difficult to govern reliably or manage cost-effectively. That’s 80% of your digital estate which is…
Metadata is the lexicon of your digital domain. Metadata is more vital than many organisations realise. AI & organisational knowledge depend on it. We literally use metadata to describe the universe: high volumes of digital information about galaxies far, far away. Without metadata, there would simply be a multitude of stars lacking the relationships & relevancy…
Knowledge is inferred using semantic & application metadata, structured by an ontology. Knowledge graphing applies probabilistic, automated reasoning to determine meaning from semantically-described content, through its context & relationship predicates as defined by a domain ontology, linking object & subject. The ontology is an evolving neural web: mapping & ranking the inferred perspectives to cohere…
If you have massive amounts of data which needs to be available across the extent of your organisation, even your ecosystem, you will need data engineering. Data engineering could be regarded as the antidote to (prevalent) organic (as opposed to purposefully architected) information flows in application-centric organisations. You need to design & deliver optimal circulation…
It seems obvious, but migrating to cloud can be a frustrating process if your data is not suitably transformed before you try the ETL process. As data volumes get bigger; formats more varied and growth, exponential, data transformation techniques are vital. Routine transformations ensure harmony of data format and target destination. But more importantly, data…
The application of Kx to seriously big time-series data as explained by an enthralling professor from the European Space Agency.
Rekognition represents a significant step forward by Amazon in the digital battle to understand and grasp unstructured content via metadata.