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| Format: | Recurso digital |
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Zenodo
2021
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| Online Access: | https://doi.org/10.5281/zenodo.15106578 |
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| _version_ | 1866901681322590208 |
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| author | Shankeshi, Raghu Murthy |
| author_facet | Shankeshi, Raghu Murthy |
| contents | <p>As the complexity and size of cloud-hosted Oracle Database environments is growing, using AI-driven automation toachieve performance, increasing the utilization of resources, decrease the operational costs is becoming a requirement. It addresses the issue of integrating artificial intelligence in the databases query optimization, indexing, workload balancing, anomaly detection and self healing processes in order to make databases more efficient. With the help of AI models, organizations can eliminate the need of doing performance tuning and accomplish time dynamic resource allocation as well as proactive handling of system anomalies, thus reducing query execution time and increasing the reliability of a database. The study then elaborates on the various advantages of having AI optimization of the database, such as the real time management of the workload, the intelligent indexing strategies, and the proactive prevention of failure. With database stability being the lifeline of any data operation, AI powered anomaly detection mechanisms provide a significant boost by determining irregular pattern and take the escalative corrective action before system performance degrades to the point of failure. Another important feature facilitating many benefits of OLAP is automated workload balancing in order to evenly distribute processing power avoid bottlenecks and optimize query throughput. The improvements of these deliver the benefits of reduced downtime, increased system resilience, and economically utilized cloud resource utilization. Additionally, AI based enterprise solution helps enterprises to realize financial efficiency by leveraging adaptive provisioning of resources on cloud optimizing expenditure in cloud. Typically database management techniques involve either over provisioning of resources or under utilization resulting in unnecessary cost. On the other hand, AI based automation is automatic to scale out the resources based upon workload requirement and it is cost effective for cloud utilization. But yet, there are challenges like data security, compliance risks, and reliance on cloud provider APIs to fully leverage the potential of the AI in the database management.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15106578 |
| institution | Zenodo |
| language | |
| publishDate | 2021 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Enhancing Oracle Database Performance with AI-Driven Automation in Cloud Environments Shankeshi, Raghu Murthy <p>As the complexity and size of cloud-hosted Oracle Database environments is growing, using AI-driven automation toachieve performance, increasing the utilization of resources, decrease the operational costs is becoming a requirement. It addresses the issue of integrating artificial intelligence in the databases query optimization, indexing, workload balancing, anomaly detection and self healing processes in order to make databases more efficient. With the help of AI models, organizations can eliminate the need of doing performance tuning and accomplish time dynamic resource allocation as well as proactive handling of system anomalies, thus reducing query execution time and increasing the reliability of a database. The study then elaborates on the various advantages of having AI optimization of the database, such as the real time management of the workload, the intelligent indexing strategies, and the proactive prevention of failure. With database stability being the lifeline of any data operation, AI powered anomaly detection mechanisms provide a significant boost by determining irregular pattern and take the escalative corrective action before system performance degrades to the point of failure. Another important feature facilitating many benefits of OLAP is automated workload balancing in order to evenly distribute processing power avoid bottlenecks and optimize query throughput. The improvements of these deliver the benefits of reduced downtime, increased system resilience, and economically utilized cloud resource utilization. Additionally, AI based enterprise solution helps enterprises to realize financial efficiency by leveraging adaptive provisioning of resources on cloud optimizing expenditure in cloud. Typically database management techniques involve either over provisioning of resources or under utilization resulting in unnecessary cost. On the other hand, AI based automation is automatic to scale out the resources based upon workload requirement and it is cost effective for cloud utilization. But yet, there are challenges like data security, compliance risks, and reliance on cloud provider APIs to fully leverage the potential of the AI in the database management.</p> |
| title | Enhancing Oracle Database Performance with AI-Driven Automation in Cloud Environments |
| url | https://doi.org/10.5281/zenodo.15106578 |