Speaker
Description
Abstract: In the context of digital transformation, data has become one of the most valuable strategic assets for contemporary organizations. Beyond facilitating routine operational activities, it plays a critical role in informing and supporting strategic decision-making processes. Organizational data may encompass a wide range of sources, including clinical research records, customer databases, analytical reports, and internal communication. Through systematic data analysis and processing, companies are able to identify inefficiencies within their operations and develop targeted strategies for improvement.
The integration of artificial intelligence into data archiving processes represents a significant advancement in the field of information management. Artificial intelligence–driven approaches enable automated classification, intelligent indexing, and advanced search capabilities, thereby substantially enhancing the efficiency, accessibility, and accuracy of archiving systems.
This study presents methods that examine the transformation and optimization of data archiving and retrieval processes through the application of artificial intelligence. In addition, it addresses potential challenges and limitations associated with the implementation of such technologies.
Keywords: Artificial Intelligence (AI), Data Backup and Recovery, Optimization