Gen AI Impact On The Database Industry Innovations
Padmaja Pulivarthy
Vol 10, Special Issue 2024
Page Number: 28 - 37
Abstract:
The future of work is a scattered workforce, and that future is here, it can be concluded from recent developments.
Consequently, it is crucial to understand that AI DB integration is not only necessary for the efficient use of AI technology and the advancement of database technology, but also for the computing of the future, which will enable the development of Intelligent Information Systems and enable more efficient and productive work. As a result, AI DB Integration will mainly support businesses, scientific and technological infrastructure, and computer-related humanitarian applications. AI DB Integration is far more significant than one may infer from its contribution to the advancement of AI and DB technology alone, given all the possible benefits at play. improvement just in DB and AI technologies. This review covered a variety of topics by focusing on a few crucial ones, such as the creation of Intelligent Database Interfaces (IDIs), Learnable databases, and Smart Query. Our investigation focused on how AI improves database efficiency through three key areas: strengthening data security, automating regular management activities, and optimizing query performance. In addition, the article provides a thorough assessment of the advancements, difficulties, and opportunities in the short- and long-term application domains where databases and artificial intelligence have converged. The review's conclusion represents the views of a few writers or specialists regarding the necessity and significance of AI database integration as well as the direction of computing in the future.
References
- Scannapieco, M. (2006). Data Quality: Concepts, Methodologies and Techniques. Data-Centric Systems and Applications. Springer.
- Bourgeois, D., & Bourgeois, D. T. (2014). Information systems development. Information Systems for Business and Beyond.
- Ramakrishnan, R., Gehrke, J., &Gehrke, J. (2003). Database management systems (Vol. 3). New York: McGraw-Hill.
- Kim, S. (2020). Artificial Intelligence and Database Systems: A Comprehensive Review. IEEE Transactions on Knowledge and Data Engineering, 32(8), 1502-1519.
- Bishop, C. M., &Nasrabadi, N. M. (2006). Pattern recognition and machine learning(Vol. 4, No. 4, p. 738). New York: Springer.
- Chen, J., Song, L., Martin, R. P., Lu, C., He, B., & Yang, Q. (2012). Towards real-time data analytics in large-scale systems. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data.
- Sun Luming, Zhang Shaomin, Ji Tao, Li Cuiping, & Chen Hong. (2019). Survey of data management techniques powered by artificial intelligence. Journal of Software,31(3), 600-619.
- GGoodfellow, I., Bengio, Y., Courville, A., &Bengio, Y. (2016). Deep learning, volume 1.
- Russell, S., & Norvig, P. (2009). Artificial Intelligence: A Modern Approach (Essex, England)
- McKay, D. P., Finin, T., & O'Hare, A. (1990, August). The intelligent database interface: Integrating AI and database systems. In Proceedings of the 1990 national conference on artificial intelligence.
- Nihalani, N., Silakari, S., & Motwani, M. (2009, July). Integration of artificial intelligence and database management system: An inventive approach for intelligent databases. In 2009 First International Conference on Computational Intelligence, Communication Systems and Networks(pp. 35-40). IEEE.
- AmitKhare1, Dr. K P Yadav2, Department of Computer Science and Engineering, Shri Venkateshwara University, Gajraula (Amroha), U.P. India, “Database Framework and Intelligent User model: A Vital analysis”
- Sadid-Al-Hasan, S. (2007, December). Design of EIDI: A cache-based interface to integrate ai and database systems with dynamism. In 2007 10th international conference on computer and information technology(pp. 1-5). IEEE.
- Nihalani, N., Silakari, S., & Motwani, M. (2011). Natural language interface for database: a brief review. International Journal of Computer Science Issues (IJCSI), 8(2), 600.
- What is Artificial Intelligence (AI)? Oracle. (n.d.). https://www.oracle.com/artificial-intelligence/what-is-ai/
- Li, G., Zhou, X., & Cao, L. (2021, June). AI meets database: AI4DB and DB4AI. In Proceedings of the 2021 International Conference on Management of Data(pp. 2859-2866).
- Reis, P., Matias, J., &Mamede, N. (1997). Edite-A Natural Language Interface to Databases A new dimension for an old approach. In Information and Communication Technologies in Tourism 1997: Proceedings of the International Conference in Edinburgh, Scotland, 1997(pp. 317-326). Springer Vienna.
- McKay, D. P., Finin, T., & O'Hare, A. (1990, August). The intelligent database interface: Integrating AI and database systems. In Proceedings of the 1990 national conference on artificial intelligence.
- Mohammed, T. A., Alhayli, S., Albawi, S., &Duru, A. D. (2018, January). Intelligent database interfacetechniques using semantic coordination. In 2018 1st International Scientific Conference of Engineering Sciences-3rd Scientific Conference of Engineering Science (ISCES)(pp. 13-17). IEEE.
- Malik, A., & Rishi, R. (2015). A domain and language construct based mapping to convert natural language query to SQL. International Journal of Computer Applications, 116(4).
- Sangeetha, J., &Hariprasad, R. (2019). An intelligent automatic query generation interface for relational databases using deep learning technique. International Journal of Speech Technology, 22, 817-825.
- Yang, Z. (2022). Machine Learning for Query Optimization. University of California, Berkeley.
- Dong, X., & Zeng, L. (2021). Research on Query Optimization of Classic Art Database Based on Artificial Intelligence and Edge Computing. Wireless Communications and Mobile Computing, 2021, 1-11.
- Zou, B., You, J., Wang, Q., Wen, X., & Jia, L. (2022). Survey on learnable databases: A machine learning perspective. Big Data Research, 27, 100304.
- [25] Brodie, M. L. (1989). Future intelligent information systems: AI and database technologies working together. In Readings in artificial intelligence and databases(pp. 623-641). Morgan Kaufmann.
- Sen, R. (2017, October 6). Oracle Launches 18C, its autonomous database and Automated Cybersecurity System. Raj Sen. https://rajsen21.wordpress.com/2017/10/06/oracle-launches-18c-its-autonomous-database-and-automated-cybersecurity-system/
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