Modern technology
The increased advancement in modern technology has led to the rising importance of big-data computing stems. Big data involves a collection of huge volumes of complex data that is difficult to process and store using traditional software and database techniques. For instance, most organizations handle huge amounts of complex data for both internal and external use; hence the processing and storage of such data becomes quite challenging. Big data computing systems help this kind of data to be processed, analyzed, and stored more efficiently. Some of the fundamental big data computing technologies include sensors, computer networks, data analysis algorithms, data storage, cloud computing facilities, and cluster computer systems (Bryant et al., 2008). These technologies play an essential role in big data and global computing.
Data generated from different sources can be collected efficiently into massive data sets through localized sensor networks, and the internet. As a result, this ensures a smooth and efficient collection of large amounts of data by companies globally. Regarding data storage, increased advancement in magnetic disk technology has dramatically reduced the cost of storing data. With this technology, vast volumes of data can be stored in one disk drive. Therefore, this facilitates efficiency in the storage of huge data volumes in digital form by both global and local companies that handle large data volumes. Cluster computer systems have currently become the widely preferred hardware configuration in intensive data computing systems. The clusters provide adequate storage capacity for huge data sets, as well as the computing power to efficiently organize data, analyze it, and respond to questions regarding various data from remote users (Bryant et al., 2008). Cluster computer systems are designed to ensure maximum efficiency and reliability in managing and analyzing massive data sets; hence global companies can benefit from them. Technological advancement has led to the creation of Cloud computing facilities that enable the storage of large data volumes over the internet. This technology allows companies to organize, store, and manage all their data over the internet, thus resulting in increased efficiency. Data analysis algorithms in big data analytics combine statistical analysis, artificial intelligence, and optimization capabilities to organize and analyze huge and complex data sets more efficiently. Some organizations machine learning in their operations to analyze massive data and predict their customer interests globally (Iqbal et al., 2020).