View source for 18078340. DATA ARCHIVAL RECOMMENDATION SYSTEMS USING ARTIFICIAL INTELLIGENCE TECHNIQUES simplified abstract (Dell Products L.P.)

=DATA ARCHIVAL RECOMMENDATION SYSTEMS USING ARTIFICIAL INTELLIGENCE TECHNIQUES=


==Organization Name==

[[:Category:Dell Products L.P.|Dell Products L.P.]]


[[Category:Dell Products L.P.]]

==Inventor(s)==

[[:Category:Dhilip S. Kumar of Bangalore (IN)|Dhilip S. Kumar of Bangalore (IN)]][[Category:Dhilip S. Kumar of Bangalore (IN)]]

[[:Category:Ponnayan Sekar of Bangalore (IN)|Ponnayan Sekar of Bangalore (IN)]][[Category:Ponnayan Sekar of Bangalore (IN)]]

==DATA ARCHIVAL RECOMMENDATION SYSTEMS USING ARTIFICIAL INTELLIGENCE TECHNIQUES - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18078340 titled 'DATA ARCHIVAL RECOMMENDATION SYSTEMS USING ARTIFICIAL INTELLIGENCE TECHNIQUES

==Simplified Explanation==
This patent application describes methods, apparatus, and storage media for data archival recommendation systems using artificial intelligence. It involves processing data from database operations across multiple storage zones, generating temporal-based archival recommendations, and taking automated actions based on these recommendations.

* The patent application focuses on data archival recommendation systems using artificial intelligence techniques.
* It involves processing data from database operations across multiple storage zones in databases.
* The system generates temporal-based data archival recommendations for database storage zones.
* Automated actions are performed based on these recommendations.

==Key Features and Innovation==
* Utilizes artificial intelligence techniques for data archival recommendations.
* Processes data from database operations across multiple storage zones.
* Generates temporal-based recommendations for data archival.
* Executes automated actions based on the generated recommendations.

==Potential Applications==
This technology can be applied in various industries such as finance, healthcare, and e-commerce for efficient data management and storage.

==Problems Solved==
Addresses the need for automated data archival recommendations based on database operations across multiple storage zones.

==Benefits==
* Improves data management efficiency.
* Enhances storage optimization.
* Reduces manual intervention in data archival processes.

==Commercial Applications==
* "Data Archival Recommendation Systems Using Artificial Intelligence" can be utilized in database management software for businesses to streamline their data storage processes and improve overall efficiency.

==Prior Art==
Readers can explore prior patents related to data archival recommendation systems and artificial intelligence techniques in database management.

==Frequently Updated Research==
Stay updated on the latest advancements in artificial intelligence technologies for data management and storage.

==Questions about Data Archival Recommendation Systems Using Artificial Intelligence==
===How does this technology improve data management processes?===
This technology enhances data management processes by automating archival recommendations based on database operations.

===What industries can benefit from this technology?===
Industries such as finance, healthcare, and e-commerce can benefit from this technology for efficient data storage and management.


==Original Abstract Submitted==

Methods, apparatus, and processor-readable storage media for data archival recommendation systems using artificial intelligence techniques are provided herein. An example computer-implemented method includes processing data associated with database operations performed across multiple database storage zones in one or more databases; generating, using one or more artificial intelligence techniques and based at least in part on the processing of data associated with the database operations performed across the multiple database storage zones, one or more temporal-based data archival recommendations for at least a portion of the multiple database storage zones in the one or more databases; and performing one or more automated actions based at least in part on the one or more temporal-based data archival recommendations.



[[Category:G06F16/11]]
[[Category:CPC_G06F16/125]]