Research for Big Data Storage and Analysis Based on Artificial Intelligence | ||
| Journal of Advanced Engineering Trends | ||
| Volume 44, Issue 2, July 2025, Pages 39-50 PDF (1.75 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/jaet.2025.297909.1293 | ||
| Authors | ||
| Rabab Hussien Mohamed* 1; Kamel Hussien Rahouma2 | ||
| 1ُElectrical Engineering Dep., Faculty of Engineering, Assiut University, Assiut, Egypt | ||
| 2Electrical Engineering Dep., Faculty of Engineering, Minia University, Minia, Egypt | ||
| Abstract | ||
| In the age of big data, users generate a huge amount of data daily due to the rapid development of technology and the internet. These data are impossible to store or process by a single machine or in a traditional way. So, the need to use distrusted storage and processing systems was an emergency, such as the Apache Hadoop system, which provides a fault-tolerant, dependable, horizontally scalable, and effective service. It is based on the Hadoop distributed file system (HDFS) and MapReduce. Also, as experts and businessmen say, business is data. The need for analysis to understand business patterns and get significant insights from the available data is growing exponentially with the huge amount of data. Various organizations require an understanding analytical principles using machine learning, data prediction, and statistical techniques. Previously, only developers could perform these tasks; however, company workers can now immediately access these capabilities with cutting-edge tools. This research aims to integrate artificial intelligence with big data storage and analysis systems, using Hadoop, PySpark, Artificial Intelligence Algorithms, and Tableau to improve data processing efficiency and provide accurate analytical insights. | ||
| Keywords | ||
| Big Data; Hadoop; Hive; Tableau; Artificial Intelligence | ||
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