Energy & Utilities Solutions
Transforming the energy sector with data and AI.
Transforming the energy sector with AI
Energy companies need a platform that integrates data from IT and OT systems and delivers AI-powered automation and insights across the business. Cloudera provides:
Hybrid access to downstream, midstream, and upstream systems for a unified view of the business.
A consistent security and governance framework that spans across environments and systems.
A low-code platform for AI that brings models to the data for low-latency inferencing at the edge and in the core.
Key use cases
- Predictive maintenance
- Smart meters
- Digital twins
Predictive maintenance
Asset uptime is critical for efficient and profitable operations in the energy sector. Predictive maintenance moves beyond reactive, remote monitoring of equipment to leverage real-time operational data from assets, sensors, and IoT devices alongside historical maintenance records to predict when failure is likely to occur.
This proactive approach significantly reduces unplanned downtime, optimizes inventory and labor costs, extends equipment lifespans, and enhances safety and operational efficiency across the grid, pipelines, and plants.
Smart meters
Smart meters generate a continuous, high-volume stream of data that is critical for delivering a connected customer experience and optimizing the grid. By capturing consumption patterns, companies can move beyond basic billing to deliver personalized insights on energy usage, cost savings, and rate plan optimization.
Analyzing this data in real time enables utility companies to accurately forecast demand, quickly detect anomalies or outages, and manage a complex network of distributed energy resources (DERs). This intelligence drives better engagement, reduces strain on customer service, and supports grid stability and modernization initiatives.
Digital twins
Digitizing physical assets allows operators to run capacity-planning scenarios, understand the impact of potential failures or maintenance actions, and more before they occur in the physical world.
Building a digital twin requires integrating data from IoT sensors, maintenance logs, operational systems, and historical records to create an accurate representation of their current state and predicted behavior. Digital twins enable greater levels of automation, risk management, and capital expenditure planning across the business.
Customers
Powering customer experiences and streamlining operations in the energy sector.
energy and utilities
Meralco
energy and utilities
PTT Oil and Retail Business
energy and utilities
Podo