Asset Monitoring Analyst
Profile Code: AL-OIL-01
- ₹10 LPA (Median Salary)
- Lecture Duration 2hrs
- Course Duration 8 Weeks
Skills You Learn: Predictive Maintenance Analytics | Asset Performance Management (APM) | SCADA & IoT Data Analysis | Reliability Engineering | Dashboarding & Reporting | Root Cause Analysis | Data Visualization Tools | Risk Assessment
Overview Video
About This Course
An Asset Monitoring Analyst in the oil & gas, energy, and utilities sector focuses on tracking the performance, health, and reliability of critical assets such as pipelines, plants, and equipment. This course equips learners with the skills to monitor KPIs like uptime, downtime, asset utilization, and maintenance performance using data-driven tools. Participants gain hands-on experience with tools like Excel, SQL, and BI dashboards, along with exposure to sensor and operational data. The program emphasizes condition monitoring, performance analysis, and predictive maintenance strategies in asset-intensive environments. Learners will understand how to identify potential failures, optimize maintenance schedules, and improve operational efficiency. By the end of the course, they are prepared for roles in asset and operations analytics, with career progression into maintenance strategy, asset management, and energy operations leadership positions.
Course Content
4 modules · 8 weeks · 2hrs/dayExcel Course
The **Excel Course** covers basic to advanced concepts for Asset Monitoring Analysts in the Oil & Gas, Energy, and Utilities industry, including workbook management, formulas, functions, data validation, sorting, filtering, conditional formatting, Pivot Tables, Pivot Charts, XLOOKUP, INDEX-MATCH, Power Query, Power Pivot, asset performance analysis, equipment utilization tracking, maintenance scheduling, downtime analysis, statistical functions, dashboards, What-If Analysis, Solver, VBA automation, KPI reporting, trend analysis, predictive maintenance reporting, operational analytics, and interactive dashboards to monitor asset health, improve equipment reliability, optimize maintenance planning, and support data-driven operational decision-making.
CMMS Course
The **CMMS Course** covers basic to advanced concepts for Asset Monitoring Analysts in the Oil & Gas, Energy, and Utilities industry, including Computerized Maintenance Management System (CMMS) fundamentals, asset registration, preventive and predictive maintenance, work order management, maintenance scheduling, equipment lifecycle management, spare parts and inventory management, asset hierarchy, condition monitoring, inspection planning, downtime tracking, maintenance history, compliance management, workflow automation, reporting, dashboard creation, KPI monitoring, mobile maintenance operations, system integration, and maintenance analytics to improve asset reliability, reduce operational downtime, and maximize equipment performance.
BI Course
The **BI Course** covers basic to advanced business intelligence concepts for Asset Monitoring Analysts in the Oil & Gas, Energy, and Utilities industry, including data integration, data transformation, data modeling, KPI development, dashboard creation, interactive visualizations, asset performance dashboards, equipment health monitoring, maintenance analytics, downtime reporting, predictive analytics, DAX fundamentals, drill-through reports, automated reporting, executive dashboards, forecasting visualization, compliance reporting, performance monitoring, data storytelling, and business intelligence techniques to transform operational and maintenance data into actionable insights for improved asset utilization, operational efficiency, and strategic decision-making.
Python Course
The **Python Course** covers basic to advanced concepts for Asset Monitoring Analysts in the Oil & Gas, Energy, and Utilities industry, including Python fundamentals, variables, data types, control statements, functions, object-oriented programming, file handling, exception handling, NumPy, Pandas, Matplotlib, data preprocessing, time-series analysis, IoT sensor data processing, predictive maintenance models, anomaly detection, machine learning fundamentals, automation scripting, API integration, reporting automation, data visualization, and performance optimization to analyze asset condition data, predict equipment failures, automate maintenance analytics, and support intelligent asset management.
Key Responsibilities
- Monitor asset performance and equipment health using IoT and SCADA data
- Analyze predictive maintenance trends and identify potential failures
- Create dashboards and reports for asset reliability metrics
- Coordinate with maintenance and operations teams to optimize asset utilization
- Ensure data accuracy and support condition-based maintenance strategies
Growth Path
Tools Used
Perfect For
Mechanical Engineering Graduates | Electrical & Instrumentation Engineers | Data & Analytics Professionals | Maintenance Engineers | Energy & Utility Sector Aspirants | Professionals Interested in Industrial IoT
Fee Structure
Mentor
Analytics Learners
Professional Analyst & Mentor
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