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4) Big data analytics and technology for healthcare organization. 3) Big data analytics and management of health surveillance systems. To find out common elements in the studies reviewed, 16 studies have been selected and clustered into 4 research areas: 1) Potentialities of big data analytics. The positive relationship between big data analytics and healthcare organization management has emerged. The study aims to map extant literature and present a framework for future scholars to further build on, and executives to be guided by. Through a systematic literature review the impact of big data analytics on healthcare management has been examined. This study aims to answer three research questions: a) What is the state of art of big data analytics adopted by healthcare organizations? b) What about the benefits for both health managers and healthcare organizations? c) What about future directions on big data analytics research in healthcare?
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The big data impact on health organization management is still not clear due to the relationship’s multi-disciplinary nature. Multiple attempts aimed at highlighting the relationship between big data analytics and benefits for healthcare organizations have been raised in the literature. unstructured) and data sources (internal and external) to guide research. In addition, this paper explores a matrix for BI data types (structured vs. The framework highlights the importance of unstructured data and discusses the need to develop BI tools for its acquisition, integration, cleanup, search, analysis, and delivery. This paper, in addition to being a tutorial, proposes a BI framework and potential research topics. Although business intelligence systems are widely used in industry, research about them is limited. The emergence of the data warehouse as a repository, advances in data cleansing, increased capabilities of hardware and software, and the emergence of the web architecture all combine to create a richer business intelligence environment than was available previously.
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Business Intelligence is used to understand the capabilities available in the firm the state of the art, trends, and future directions in the markets, the technologies, and the regulatory environment in which the firm competes and the actions of competitors and the implications of these actions. The objective is to improve the timeliness and quality of inputs to the decision process. Business intelligence systems combine operational data with analytical tools to present complex and competitive information to planners and decision makers.
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