Converting Data into Decisions: From Where start out
Posted by admin_metricarts
on martes septiembre 2046, 2011
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It has become almost a commonplace of the discourse on information technology (IT) paradigm of transforming data into information and of these, in turn, into knowledge. However, to review progress on these issues within organizations, one can see that efforts often lack vision and sustainability. Clear indication of this is the tendency to assume that the project is optimal to concatenate stages perfectly executed more than if you arrive in port in the stipulated time and cost.

The business intelligence (BI), described by Howard Dresner in 1989, but was not a significant technical advance in the theory of databases and statistics, some of their mothers sciences does provide, in these terms, a major change , putting the effectiveness in supporting decision-making about any other sub-goal.

From where start out

Given the recurring problem of integrating multiple data sources for the generation of reports or studies, the first solution that could arise is to replace the source systems for a major new system to do this work.However, this approach has proved impractical and very slow, thus losing the opportunity of information and, therefore, support the decision making becomes ineffective.

Since the early nineties, Bill Inmon defined a solution to this problem: the implementation of a separate storeof data (which consists of integrated data repository whose sole purpose is to support decision making), now a cornerstone in the BI process.

This introduces a large change in vision on information management, bringing business criteria for the management of information systems. In this sense, today we can see how some companies replaceunreliable data sources for estimates, create indicators, discard irrelevant variables and even allow smallanalytical mismatch in your repositories, as not relevantly alter the process of making decisions and reduceuncertainty. At present there are some companies in Chile that have very successfully implemented this vision.

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Two objectives: Increase Value and Reduce Risk

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