OPTIMIZING DATA GOVERNANCE IN INFORMATION MANAGEMENT SYSTEMSTHROUGH ARTIFICIAL INTELLIGENCES IN PUNT LAND SOMALIA

Abstract The exponential growth of digital data in recent years has changed how businesses function and make decisions. When processing enormous amounts of data, from client information to operational records, information management solutions are crucial. Traditional approaches to data governance within these information management systems are showing to be insufficient, though, as the volume and complexity of data keep growing.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-01
DOI
https://doi.org/10.5281/zenodo.14949979
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

OPTIMIZING DATA GOVERNANCE IN INFORMATION MANAGEMENT SYSTEMSTHROUGH ARTIFICIAL INTELLIGENCES IN PUNT LAND SOMALIA

Zenodo (CERN European Organization for Nuclear Research)
Data Quality and Management
article

OPTIMIZING DATA GOVERNANCE IN INFORMATION MANAGEMENT SYSTEMSTHROUGH ARTIFICIAL INTELLIGENCES IN PUNT LAND SOMALIA

article en

Abstract

Abstract The exponential growth of digital data in recent years has changed how businesses function and make decisions. When processing enormous amounts of data, from client information to operational records, information management solutions are crucial. Traditional approaches to data governance within these information management systems are showing to be insufficient, though, as the volume and complexity of data keep growing.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 43%
Data Quality and Management
DOIOpen Access PDFOpenAlex
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OPTIMIZING DATA GOVERNANCE IN INFORMATION MANAGEMENT SYSTEMSTHROUGH ARTIFICIAL INTELLIGENCES IN PUNT LAND SOMALIA · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS