公开(公告)号：US20240249301A1

公开(公告)日：2024-07-25

申请号：US18156764

申请日：2023-01-19

Applicant: Google LLC

Inventor： Michael Yang Liu ,  Richard A. Maher ,  Edward Chou ,  Srirama Koneru ,  Batool Nadeem Husain ,  Cheolmin Kim

IPC: G06Q30/0203 ,  G06Q30/0201

CPC classification number: G06Q30/0203 ,  G06Q30/0206

Abstract: An aspect of the disclosed technology is a scalable method to derive drivers of change for composite metrics (e.g., cost metrics and ratio metrics) in a time series data set. The disclosed technology comprises an automated mechanism that enables identification and deciphering of one or more drivers, e.g., the largest contributors, or a composite metric change in a scalable manner.

公开(公告)号：US20240264986A1

公开(公告)日：2024-08-08

申请号：US18098467

申请日：2023-01-18

Applicant: Google LLC

Inventor： Michael Yang Liu ,  Abhijit Belapurkar ,  Abhishek Verma ,  Bhaswanth Uppalaguptam ,  Edward Chou ,  Michael Jun ,  Pramod Madabhushi ,  Richard A. Maher ,  Spiro Michaylov ,  Srirama Koneru ,  Nicole Pizarro

IPC: G06F16/215 ,  G06F16/23 ,  G06F16/26

CPC classification number: G06F16/215 ,  G06F16/2365 ,  G06F16/26

Abstract: A mechanism that flags and detects inaccurate or bad data, and annotates the flagged data with automatically generated metadata that may then be provided to end users (e.g., resource managers, service owners, finance analysts, data scientists, executives, etc.) via an application stack. The automatic annotations comprise quality annotations that may include data freshness, correctness, and/or completeness.

公开(公告)号：US12015527B1

公开(公告)日：2024-06-18

申请号：US18170027

申请日：2023-02-16

Applicant: Google LLC

Inventor： Michael Yang Liu ,  Subhashish Roy ,  Srinivas Vaidyanathan ,  Anurag Kumar Singh ,  Arvind Sundararajan ,  Michael Sun Yu ,  Srirama Koneru ,  Spiro Michaylov ,  Neduvelil Vinod Menon ,  Shashwat Rastogi

IPC: G06F15/16 ,  H04L41/0894 ,  H04L41/0897

CPC classification number: H04L41/0897 ,  H04L41/0894

Abstract: Maintaining an organizational hierarchy by receiving data indicative of computing resource consumption by one or more leaf nodes, wherein the leaf nodes are part of a hierarchy including the leaf nodes and higher level nodes; and generating one or more modifications for the hierarchy based on the data indicative of computing resource consumption.