An Effective Method for Managing Voluminous Data: Reducing Data to Significant Size for Efficient Results

摘要

The emergence of large, complex datasets has made effective data processing a challenging task for existing methods. In spite of this, organizing large datasets is a difficult task regardless of the technologies. However, this research proposes effective methods that can be utilized for managing, analyzing, and extracting useful information from large, diverse data. We propose an efficient way to catalogue and retrieve data by creating a directory file. More specifically, an improved method that would allow file retrieval based on its time and date. We also offer an efficient data reduction method that effectively condenses the amount of data. Moreover, the algorithm enable users to store the desired amount of data in a file and decrease the time in which observations are retrieved for processing. This is achieved by using a reduced standard deviation range to minimize the original data to a significant size.