Organizations need to use a structured view of information to improve their DM process.
To achieve this structured view, they have to collect and store data, perform an analysis, and transform the results into useful and valuable information. To perform these analytical and transformational processes, it is necessary to make use of an appropriate environment composed of a large and generalist repository, a processor core with the appropriate intelligence BI, and a UI . The repository must be filled with data originating from many different kinds of ext and int DS These repositories are the DW generalists and DM and most recently, BD.
The BD concept and its applications have emerged from the increasing volumes of ext and int data from organizations that are differentiated from other data? bases in 4Vs : volume, velocity, variety, and value. Volume considers the data amount, velocity refers to the speediness with which data may be analyzed and processed, variety describes the different kinds and sources of data that may be structured, and value refers to valuable discoveries hidden in great datasets Big Data has the potential to aid in identifying opportunities related to decision in the intelligence phase of Simon’s model. In some cases, the stored data may be used to aid the decision-making process. In this context, the term “intelligence” refers to knowledge discovery with mining algorithms.
In this way, Big Data use can be aligned with the application of Business Intelligence (BI) tools to provide an intelligent aid for organizational processes. The data necessary to obtain the business perceptions must be acquired, filtered, stored, and analyzed after the available data are heterogeneous and in a great volume. The processes of filtering and analysis of the data are very complex, because of that it is necessary the use BI strategies and tools. The main proposal of the present study is to develop an investigation that describes the roles of Big Data, and BI in the decision-making process, and to provide researchers and practitioners with a clear vision of the challenges and opportunities of applying data storage technologies so that new knowledge can be discovered.
The sequence of this work is as follows. Section 2 provides a background for BD and some of its applications. Section 3 introduces the concept of DSS. Section 4 conceptutilize BI and presents its organizational and technological components. Section 5 presents a scheme for the integration between Big Data, BI, decision structuring and making process, and organizational learning.
Section 6 contains a discussion about the integration perspective of the decision-making process, according the scheme presented in Sect. 5. Finally, the conclusion presents the limitations of this study and highlights the insights this work has gained