Our Knowledge Repository

Key to enabling Advanced Analytics

The value of potential analytics is highly dependent on the depth of information extraction and integration that can be derived from the data. One of the key benefits of natural language processing models (NLP), is the understanding of “subjects”—text and table-based information in particular.

NLP can provide insights into the distribution of features within the data, and extract and embed the underlying knowledge into a highly refined data architecture.

A Knowledge Repository is not a duplication of data—it is an extraction of relevant information attributes and features, which are then embedded and classified into a complex set of associations and correlations across other integrated data.

From
Warehouses…

And
Data Centres,
And Data Lakes…

To An Integrated Knowledge Repository

Key to Enabling
Advanced Analytics

A Knowledge Repository is not a duplication of data—it is an extraction of relevant information attributes and features, which are then embedded and classified into a complex set of associations and correlations across other integrated data.

From
Warehouses…

And
Data Centres,
And Data Lakes…

To An Integrated Knowledge Repository

Key to Enabling
Advanced Analytics

Resource Exploration Data Type Example

As data moves through our NLP models, the platform’s different processors transform engineered or extracted features into relevant data attributes (Data Architecture Features), this extracted data is then run through a classification process that builds a persistent map of the correlations across every data point embedded into the platform. This new knowledge is held persistently in the platform. This pre-analytic processing, is a key reason why our analytics is so lightning fast. We’ve done a large chunk of the analytics upfront.