Covid-19 Effects on Libraries Goes Beyond Books: Lead City University in Perspective

Information is a resource that is naturally needed in all aspects of human endeavors and the library, as an institution responsible for the acquisition, organization and dissemination of information is highly sought by information users. However, the outbreak of the COVID-19 pandemic has led to the closure or restriction of access to libraries all over the world, of which the Lead City University Library was not an exception. This article contends that the restrictions caused by the COVID-19 pandemic has a wide ranging impact on the library and its users that goes beyond lack of access to books and other information resources. This is because the library is a social institution which has become more of a community center where people can come together not only to access information but also to learn new skills and make new connections in their quest for enlightenment, leisure, up skilling, learning, re-learning and self-fulfillment. To ameliorate this situation and maintain the relevance of the library, the study recommended that it is important that academic libraries invest more on Information Technology infrastructures and electronic resources. Librarians also need to acquire improved ICT skills needed for virtual interaction with information users which is sacrosanct in this era of the new normal

A data transformation model for relational and non-relational data

The information systems that support small, medium, and large organisations need data transformation solutions from multiple data sources to fulfill the requirements of new applications and decision-making to stay competitive. Relational data is the foundation for the majority of applications programme, whereas non-relational data is the foundation for the majority of newly produced applications. The relational model is the most elegant one; nonetheless, this kind of database has a drawback when it comes to managing very large volumes of data. Because they can handle massive volumes of data, non-relational databases have evolved into relational database substitutes. The key issue is that rules for data transformation processes across various data types are becoming less well-defined, leading to a steady decline in data quality. Therefore, to handle relational and non-relational data and satisfy the requirements for data quality, an empirical model in this domain knowledge is required. This study seeks to develop a data transformation model used for different data sources while satisfying data quality requirements, especially the transformation processes in relational and non-relational model, named Data Transformation with Two ETL Phases and Central-Library (DTTEPC). The different stages and methods in the developed model are used to transform the metadata information and stored data from relational to non-relational systems, and vice versa. The model is developed and validated through expert review, and the prototype based on the final version is employed in two case studies: education and healthcare. The results of the usability test demonstrate that the developed model is capable of transforming metadata data and stored data across systems. So enhancing the information systems in various organizations through data transformation solutions. The DTTEPC model improved the integrity and completeness of the data transformation processes. Moreover, supports decision-makers by utilizing information from various sources and systems in real-time demands