Invention Grant
- Patent Title: Machine learning systems for ETL data streams
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Application No.: US17243946Application Date: 2021-04-29
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Publication No.: US11714721B2Publication Date: 2023-08-01
- Inventor: Aqa Muhammad Ziaul Ehsan , Kevin Luong Tran
- Applicant: Bank of America Corporation
- Applicant Address: US NC Charlotte
- Assignee: Bank of America Corporation
- Current Assignee: Bank of America Corporation
- Current Assignee Address: US NC Charlotte
- Agency: Weiss & Arons LLP
- Main IPC: G06F11/00
- IPC: G06F11/00 ; G06F11/14 ; G06F16/25 ; G06F16/215 ; G06N20/00 ; G06F11/34 ; G06F9/50

Abstract:
Apparatus and methods an artificial intelligence method of reducing failure in an informational flow of a data stream controlled by an Extract Transform Load process using a machine learning (“ML”) model training system are provided. The method may include deploying a software sensor that periodically captures data points for an extract job executed during an extract phase of the process. The method may also include building a behavior profile concurrently with the receipt of each of the data points. The method may further include comparing the behavior profile to behavior profiles stored in an Adverse Behavior Model database and behavior profiles stored in a Normal Behavior Model database. When the behavior profile is determined to have a threshold number of match points matching the behavior profile to behavior profiles in the Adverse Behavior Model database, the method may include increasing a target database storage capacity.
Public/Granted literature
- US20220350704A1 MACHINE LEARNING SYSTEMS FOR ETL DATA STREAMS Public/Granted day:2022-11-03
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