ETL is undeniably application-centric, but even in the era of cloud, there are still key areas where we can help de-stress your ETL project or migration. Finding data residing in ERP or CRM applications relies on understanding the underlying data models which is no small task as ERP vendors typically tend to be rather opaque…
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…
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,…
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…
A knowledge graph can be thought of as a search engine on steroids, though its application goes well beyond that to chatbots, product recommenders and autonomous systems. Semantics make it possible for the knowledge graph to carry out probabilistic analysis of content: ranking meaning against search criteria on the basis of salience referenced against various…
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…
Incorvus’ data management follows a logical path through the data lifecycle to prepare your data before poor quality or suitability distorts information architecture & analytics’ visualisation – or beyond that AI or ML! Looking after data repositories, infrastructure, processing and practices, as distinct from the stewardship of the data itself, should create organisational confidence. But…
Generate internal credibility and external value from continuously curated and well-governed data which can be presented, realise value and meet compliance tests. When data is presented, so is your reputation. Presented data must stand the test of time as well as meet immediate deadlines. Do you have overlapping or duplicate reports, all draining the same…
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…
Once you have clean data, why stint your investment? Curation isn’t just about certain datasets (as many would have it) nor just about metadata, but about sustaining the health & value of your entire data-fuelled corporate cardiovascular system. Just like the human body, a blockage anywhere in the system can prove fatal. Think again about…