Review shows effective HR planning and corporate communication in steel industries, highlighting big data's role.
Human resource is a prime variable without which the entire equation of profit and productivity becomes imbalanced. It can appreciate in value. Entrusted with the successful operation of a business, human resource management is an extremely complex and demanding duty. According to Farndale et al. (2010) and Troshani et al. (2011), HRIS systems that support decision-making about essential HR functions can be used to create strategic value." Strategic planners could not have predicted future labor supply and demand without the data provided by HRIS. Planning for human resources is the process by which problems with them are connected to the business requirements of the company. The results of this study will help future HRIS users utilize the system's functionalities for HR planning to the fullest instead of just using it for administrative tasks. The two HRD subsystems that make up the study framework are HRIS Corporate Communication and HRIS Human Resource Planning. Better plans have a big impact on a company's survival and performance, which is why businesses have started concentrating on tactfully use of its Human Resource and other resources with a concern for its customers satisfactions. Organizations were better equipped to handle the intense competition brought on by globalization when they applied strategic management with information systems. There are several examples of businesses that have failed and others that have flourished. With the advent of big data, businesses now handle, analyze, and derive conclusions from massive amounts of data in a fundamentally different way. An extensive overview of big data is provided, along with information on its applications, challenges, and strategies for handling its complexities. The study looks at all the industries that depend on big data, including government, healthcare, industry, and education. It also examines the challenges that big data presents, such as data storage, scalability, privacy, and security. These problems are addressed by a wide range of technologies and techniques, including cloud computing, machine learning, and data mining.
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Chowdhury et al. (2024) studied this question.
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