View source for Oracle international corporation (20240126564). CONFIGURING AN ENRICHED DATA METRICS PIPELINE simplified abstract

=CONFIGURING AN ENRICHED DATA METRICS PIPELINE=


==Organization Name==

[[:Category:oracle international corporation|oracle international corporation]]


[[Category:oracle international corporation]]

==Inventor(s)==

[[:Category:Swapnil Sinvhal of Belmont CA (US)|Swapnil Sinvhal of Belmont CA (US)]][[Category:Swapnil Sinvhal of Belmont CA (US)]]

[[:Category:Elizabeth Li of Sugar Land TX (US)|Elizabeth Li of Sugar Land TX (US)]][[Category:Elizabeth Li of Sugar Land TX (US)]]

==CONFIGURING AN ENRICHED DATA METRICS PIPELINE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240126564 titled 'CONFIGURING AN ENRICHED DATA METRICS PIPELINE

==Simplified Explanation==

The abstract describes techniques for configuring an enriched data metrics pipeline (DMP) for nodes of a heterogeneous computing platform. The unenriched DMP provides node-level unenriched data to a service, which generates node-level data metrics. The enriched DMP is configured based on node configuration data to provide node-level enriched data to the service less frequently, allowing the service to generate fleet-level data metrics.

* Obtaining node configuration data for different kinds of nodes on a heterogeneous computing platform
* Configuring an enriched data metrics pipeline to provide node-level enriched data less frequently than unenriched data
* Generating fleet-level data metrics based on node-level enriched data

== Potential Applications ==
The technology can be applied in various industries such as data analytics, IoT, cloud computing, and performance monitoring.

== Problems Solved ==
1. Efficient data processing and analysis for heterogeneous computing platforms
2. Generating fleet-level data metrics from node-level enriched data

== Benefits ==
1. Improved performance monitoring and optimization
2. Enhanced data analytics capabilities
3. Streamlined data processing workflows

== Potential Commercial Applications ==
Optimizing cloud computing infrastructure, enhancing IoT data analytics, improving performance monitoring in data centers.

== Possible Prior Art ==
Prior art may include existing data processing and analytics tools for heterogeneous computing platforms, as well as techniques for generating fleet-level data metrics.

== Unanswered Questions ==

=== How does the technology handle real-time data processing? ===
The abstract does not mention the real-time processing capabilities of the enriched DMP. 

=== What security measures are in place to protect the data being processed? ===
The abstract does not address the security aspects of the data metrics pipeline.


==Original Abstract Submitted==

techniques for configuring an enriched data metrics pipeline (dmp) include: obtaining node configuration data associated with an unenriched dmp for nodes of a heterogeneous computing platform, including (a) a first kind of node including an application programming interface (api) for obtaining unenriched data associated with the first kind of node and (b) a second kind of node including an api for obtaining unenriched data associated with the second kind of node; the unenriched dmp being configured to provide node-level unenriched data to a service according to a first schedule; the service being configured to generate node-level data metrics based on the unenriched data; based on the node configuration data, configuring an enriched dmp to provide node-level enriched data to the service according to a second schedule that is less frequent than the first schedule; the service being configured to generate fleet-level data metrics based on the node-level enriched data.



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