OMB Individually Reported
EDAV Azure DataFactory - Pipeline failure Analysis
Low riskExact public inventory row
Description
There are over 4,000 pipelines which provide logs of their status. Manual review is highly time-consuming and error prone due to the scale of logs.
Detailed example
Logs of the Data Factory pipelines and analysis of the various information from the data pipelines including recommended next steps to support staff in solving potential challenges maintaining these data pipelines.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Benefits include improved quality of summaries of logs and additional information that is available faster than traditional manual processes.
Controls / human review
ATO: Yes; PIA: Not published