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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

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Paper Title: Data Silos - A Roadblock for AIOps
Authors Name: Subhadip Kumar
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IJRTI_188833
Published Paper Id: IJRTI2401007
Published In: Volume 9 Issue 1, January-2024
DOI: https://doi.org/10.5281/zenodo.10471800
Abstract: Using artificial intelligence to manage IT operations, also known as AIOps, is a trend that has attracted a lot of interest and anticipation in recent years. The challenge in IT operations is to run steady-state operations without disruption as well as support agility" can be rephrased as "IT operations face the challenge of maintaining steady-state operations while also supporting agility [11]. AIOps assists in bridging the gap between the demand for IT operations and the ability of humans to meet that demand. However, it is not easy to apply AIOps in current organizational settings. Data Centralization is a major obstacle for adopting AIOps, according to a recent survey by Cisco [1]. The survey, which involved 8,161 senior business leaders from organizations with more than 500 employees, found that 81% of them acknowledged that their data was scattered across different silos within their organizations. This paper illustrates the topic of data silos, their causes, consequences, and solutions.
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Cite Article: "Data Silos - A Roadblock for AIOps", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 1, page no.33 - 39, January-2024, Available :http://www.ijrti.org/papers/IJRTI2401007.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2401007
Registration ID:188833
Published In: Volume 9 Issue 1, January-2024
DOI (Digital Object Identifier): https://doi.org/10.5281/zenodo.10471800
Page No: 33 - 39
Country: Blaine, Minnesota, USA
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2401007
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2401007
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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