Data Analysis and Related Applications, Volume 1

14A Method of Big Data Collection and Normalization for Electronic Engineering Applications

Data collection and storage have become the greatest challenges and tedious processes in data science engineering. Data from various nodes (sensors, bridges, switches, hubs, etc.) in the environment or in a particular system is collected at the nodes from which they arrive at the storage point. These types of operations need a separate workforce to monitor the whole process of data handling. This proposed work mainly focuses on the data analytics of creating normalized data from unprocessed data. This reduces the manipulation of data when it is of a different form. The data may be realistic depending on the system which produces it. The normal distribution applies to the collected data to create a dataset that is distributed over the continuous probability density function. It extends up to infinity in both directions of the axes. The proposed work provides an easy storage and data retrieval method in the case of large data volumes. The proposed data recovery is compliant with the conventional data collection methods. This type of data interpretation provides security and confidentiality of the user’s data.

14.1. Introduction

Data science has long been prevalent in all areas of science in this digital era. Data science is an interdisciplinary field that fuses science and technologies by using algorithms, tasks and devices to extract usable data from raw unstructured data. The extracted ...