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Knowledge Engineering & Business Intelligence

October 30, 2010 Leave a comment

We say “Knowledge Engineering”; we then speak about “Business Intelligence”. Here are the Megladons, Great Whites and what’s in between!

Knowledge Engineering (KE) is an engineering discipline that involves integrating human knowledge into systems, frameworks, methods and processes in order to solve complex problems normally requiring a high level of human expertise. Business intelligence (BI) refers to computer-based techniques used in spotting, digging-out, and analyzing business data. BI technologies provide historical, current, and predictive views of business operations.

With complex data sets businesses keep producing over transactions of varied kind and their kindred; BI at the first layer and KE at the next layer provide complex intelligence, decision support from the data sets. Knowledge Engineering is the collective stack of ‘Expertise + BI + Research’ which results in recommendations and solutions for evolving businesses from a 360° Perspective.
There is this deep need to research and develop process and systems to extract data from varied t’eco-systems, store, tune for building dominoes, and present data structures for expert human intervention from a SME perspective. EHI enables to connect and overlay these mined>domino-ed data sets with a solution stack driving complex decision support, savior strategies, threat negations, process frameworks that redefines and edifies. BI technically has a lot to contribute especially through its native adoption of Warehousing and Analytics systems and processes. This warehousing and analytics does augment research efforts for the EHI tasks; “What is” is what is needed in varies perspectives in comprehending the data stack and this the prelude to KE. How the data stack is structured involves EHI to identify the sources and to build relativity.

There is no dearth for systems and process available in the market today; from solutions and services ‘dime-a-dozen’ to what the market leaders have in offering the lack-the gap-the missing link has always been EHI processes with its diagnostic, anatomic, molecular specifics to structure business evolutions. Be it a profit Kalashnikov of a corporation or a loss attracting black hole enterprise, investments over BI cannot be complete if you are not adopting Knowledge Engineering practices. The need… well we have them already and one tailored KE framework will certainly nuke rigidity and blow away the comprehension veils.

– Jesu Valiant

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