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Top1. Introduction
In the ongoing twenty century extreme digital automation, the cloud computing technologies were quickly configured and adopted by several organizations, businesses and individuals to provide the perception of resource management, sharing and distribution across enterprise platforms(Yadav & Behera, 2020). The cloud infrastructure approaches exist usually to merge services and synchronize data through several Internet of Things (IoTs) computing platforms, establishing unification that will enable data aggregation through different cloud models (Cai, Xu, Jiang, & Vasilakos, 2016). Amalgamating public cloud services and private clouds to form a coupled data center as a hybrid is a novel characterization of commercial business computing initiatives. Commercial organization investment in enterprise data warehouse development were necessitated by cloud computing technology innovation and practices, increasing the efficiency of the organizational business intelligence while reducing the operational costs, across organization Information Technology (IT) investment ecosystem (Nazir et al., 2020). As most of the business organizations, such as healthcare sector are customer oriented and database driven, the demand for cloud enterprise data warehousing became increasingly necessary to keep the life wire which is information, open for business decision and logistics planning. This approach satisfied business priorities that motivated investment in the modern enterprise data warehouse development with expectation of increasingly investment and performances as most businesses are database centred and customer service oriented(Nagy, Oláh, Erdei, Máté, & Popp, 2018).
The IT investment which implied the application of extreme information computation and data processing operations requiring computer hardware, software and lifeware that deals with the indexing, filing, storage, retrieval, sharing, and use of business information system, organizational data, technology and understanding of communication techniques and uses for corporate and operational decision making,(Hassanalieragh et al., 2015) . The enterprise databases are used to deliver essential service items being monitored from the logistics station to the destination with accurate data governance and precise operational feedback. The enterprise data warehouse (EDW) usually involved the aggregation of database repositories, that centralizes the organization business's information system for data governance arising from multiple heterogeneous sources and applications, and making information available for analytics and for utility around the organization business ecosystem(Dubey et al., 2020). The EDWs can be incorporated and accommodated on the premise server or hosted within the enterprise cloud computing arrangement. In this manner, information captured within the data warehouse can be one of the business organization indispensable assets, as it symbolizes what business is known with, its employees, its customers, its vendors, and other essential aspect of organizational Information and database system. The EDW has become a standard component of the corporate data architecture, representing an aspect of the organizational functional split(Lnenicka & Komarkova, 2019). Fundamentally, every business organization is a social structure containing separate activities and specialized logistics function, which characterizes an essential aspect of business life wire for competitive survival and administrative convenience (Ortiz-Villajos & Sotoca, 2018).