Data Engineering for Decision Science

Business intelligence (BI) systems are the one that gather, store, and process data to turn it into information that’s meaningful and relevant for decision-making in businesses and organizations. In today’s times, the organizations are finding various ways to find meaning from the data that they record in order to gain an insight for the future. As this happens, the engineering of BI systems is gaining importance amongst the organizations alike.

For successful engineering, its development, use and evolution of a BI system, requires a deep understanding of the elements of the decision making processes in the organization. At the same time, it is very important for the BI developers to know and understand the important KPI’s that influence the business decisions and form the basis of parameters to monitor the organizational performance. The BI developers also need to understand the source of data, the ways in which the data has to be transformed, its analysis and how the data can be acquired and cleaned. It is also important to understand how the quality of data can be improved and how heterogeneous data can be used together. The identification and analysis of concepts and relevant relations for the various steps in the engineering of BI systems, the conceptual modeling of requirements for BI systems, volume of the data used and produced by them, of the transformations and analyses of data, are only some of the topics to which researchers and practitioners of conceptual modeling can contribute, in the aim of constructing theoretically sound and practically applicable models and reasoning facilities to support the engineering of BI systems.

The goal to initiate discussions and studies in ontologies, modeling languages, and reasoning methods relevant for the engineering of requirements for, and the engineering and specification of BI systems. These modeling and reasoning techniques will provide more precise and rich information for the end-user, bridging the gap between technical and user-centric tools for Business Intelligence.

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