Data Analytics for Predictive Maintenance for Business Intelligence for Operational Efficiency
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Abstract
Abstract—Predictive maintenance is transforming the
contemporary business world with the help of data analytics and
BI. A predictive maintenance-based strategy enhances
efficiency, optimizes the maintenance schedules, and results in a
drastic reduction in unplanned downtime. To show the
measurable impact of predictive maintenance strategies, the
study was anchored on case studies and a comparison of various
leading IT companies, including Intel, Google, Microsoft, and
Cisco. These companies saved money, downtime, and increased
service reliability with the help of machine learning, Internet of
Things (IoT) enabled sensors, and instant processing of the data.
The study relies on data sets of real operational metrics to
demonstrate the role of predictive analytics and BI dashboards
in achieving insightful information on proactive decisionmaking. As per the findings, predictive maintenance augments
asset life, elevates client satisfaction, and dramatically reduces
the cost of operations. This paper reveals the importance of
predictive maintenance driven by data in future-ready business
intelligence systems.
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