Optimization of Big Data Processing and Analysis Processes in the Field of Data Analytics Through the Integration of Data Engineering and Artificial Intelligence

In this article, we provide an overview of the current state of artificial intelligence (AI) and big data analytics, which are the most needed needs of our age. This report is designed to provide an overview of the latest research and achievements in this rapidly growing field and to highlight, check and complement the many ways in which AI can be combined to improve data. The most important developments in the field of data analysis demonstrate the development of machine learning models, the importance of explaining AI, and the use of AI in computing. Methodology: for this research we have analyse the latest trend in the related field of AI and data engineering. We have short listed nine main papers for this report. Meta-analysis requires the use of descriptive and/or statistical methods to collect data from multiple studies on a particular topic. These ideas help build knowledge from many studies in both qualitative and quantitative ways. Results: The article provides an overview of the complexities of integrating large amounts of data with intelligence, exploring topics such as data integrity, social and ethical issues. Additionally, it introduces new applications across multiple industries and reveals opportunities to transform environmental monitoring, supply chain operations, cybersecurity, and health monitoring. Overall, this article provides the reader with an in-depth understanding of the latest advances and challenges in data mining and intelligence-based analysis. Conclusion: It contributes to the ongoing debate on how AI can be used to gain meaningful insights from massive data sets, and provides a forward-looking perspective on the potential impacts on multiple sectors of the economy and society in general. Another new concept that expresses the openness of AI algorithms is descriptive intelligence (XAI). Understanding and interpreting intelligence decisions is important because it plays an important role in information processing, especially in areas that require compliance with ethical and legal standards.