Difference between revisions of "Portal:Business Intelligence/Introduction"

From IMSMA Wiki
Jump to: navigation, search
 
(16 intermediate revisions by 2 users not shown)
Line 1: Line 1:
Business intelligence (BI) is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information. While operational systems - such as {{IMSMANG}} and many others - are designed and optimised for data entry, updates, etc., a BI system is usually designed for analysing and visualising data. It is thus a read-only system.
+
[[Image:KPI.png|left|75px]]
 
+
Business intelligence (BI) is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information [http://en.wikipedia.org/wiki/Business_intelligence]. While operational systems - such as {{IMSMANG}} and many others - are designed and optimised for data entry and updates, a BI system is read-only and designed for '''analysing''' and '''visualising''' data. The overall objective is to inform the decision making process, thus allow for evidence-based decision making. An important criterion of the underlying data is its '''quality''' - meaningful analysis can only be achieved if the input data is accurate, complete, and of known quality.
The Mine Action INTelligence Tool (MINT) has been introduced to allow analysing, visualising and reporting on mine action data from various sources. It is a tool and service provided by the GICHD to the wider mine action community.
 
 
 
[[Image:MINT_scope.png|center|600px|''Scope of MINT'']]
 

Latest revision as of 20:56, 20 February 2020

KPI.png

Business intelligence (BI) is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information [1]. While operational systems - such as IMSMANG and many others - are designed and optimised for data entry and updates, a BI system is read-only and designed for analysing and visualising data. The overall objective is to inform the decision making process, thus allow for evidence-based decision making. An important criterion of the underlying data is its quality - meaningful analysis can only be achieved if the input data is accurate, complete, and of known quality.