In recent decades, the markets have benefited from advances in information technology to automate many processes, which, however, is no longer sufficient to achieve a sustainable competitive advantage. Today’s markets require a new set of skills enabling more advantage of these developments legacies.
Terms like datwarehouse, data marts, OLAP and data mining are recurrent, but said any of these efforts in structure and development time is difficult and intimidating, considering the natural and constant change of markets and therefore the information requirements .
It is important to understand that none of these tools itself can solve the equation.
Consider, for example, the existence of a data warehouse with some marts from which it has been possible to develop some customer analysis and market segmentation studies. Both as a data warehouse data marts allow this generation of knowledge, however, lack the necessary elements to efficiently transform into action, therefore, will require other elements capable of providing real-time integrated information about clients.
This example illustrates the need for an architecture capable of orchestrating these efforts. Bill Inmon, considered the father of data warehousing, describes this interaction as an evolving ecosystem while changing its components and describes its architecture teacher and corporate information factory, which covers all processing of data in an organization, with the constituent parts legacy systems and core transactional stores operational data stores (such as data warehouse or data marts), and support systems making such decisions themselves in correct synchronization, rather than a long and costly overlapping technologies.
People and processes that interact with corporate information factory complete the ecosystem and are, in general, the most difficult to address, consider involving, among others, corporate culture and change management policies.
Companies that have centrally managed information systems have to address the challenge of the existence of datamarts-managed in a distributed way, very close to the business line it supports.
Two objectives: Increase Value and Reduce Risk