Data governance and AI become central to every operational decision.
From the global energy crisis to internal pressures for green growth and operational efficiency, the energy industry is adapting at an unprecedented pace. Data governance and AI are at the heart of every operational decision.
Data becomes a strategic asset
In the digital age, data is the core element, likened to the second electricity that fuels factory operations. Every day, power plants, monitoring centers, and transmission stations generate millions of data streams from sensors, cameras, monitoring control systems, and data collection systems. Proper processing, storage, and exploitation of this data source will determine operational efficiency and forecasting capabilities throughout the entire energy supply chain.
However, in reality, many businesses and factories are still facing "bottlenecks" in data management with discrete, dispersed systems that are not seamlessly connected to form a multidimensional picture of production and business activities. This is not only a major barrier in the digital transformation process, but also reduces management efficiency, hinders decision-making speed and limits long-term competitiveness.
Fragmented systems are the bottleneck of digital transformation. Most businesses are still operating on multiple separate systems. Data is scattered and lacks overall planning, causing great difficulties in management and synchronization. The use of data from multiple heterogeneous sources from software systems, manual input, to separate tracking files.
At the same time, the lack of consistency in indicators and calculation methods as well as in-depth data mining tools also makes assessment and measurement reporting unreliable, reducing the effectiveness of management decisions.
In particular, many businesses only focus on digitizing processes without actually investing in digitizing data. As a result, a lot of unstructured data appears in the form of attached files, wasting storage resources and making it difficult to exploit effectively.
The lack of master data - a collection of core data about business assets such as materials, equipment, human resources, finance, etc. - becomes a barrier to standardizing the entire system, causing waste of resources and incorrect information.
Therefore, businesses need to consider data as a strategic asset of the business, the foundation for all management and development decisions, and at the same time build a clear data strategy, from defining system architecture, standardizing data structure, to deploying appropriate technology and tools so that data truly becomes the "digital heart" of the business.
Experience in building a systematic data strategy
Sharing practical experience with energy enterprises, Mr. Nguyen Chi Linh, representative of Viettel Enterprise Solutions Corporation ( Viettel Solutions), shared the approach based on "5 core questions" to help enterprises determine data strategies, including: identifying existing data assets; clearly understanding data needs for business and management; effectively managing and storing critical data; ensuring "correct - sufficient - clean - alive" data; building multi-dimensional reports, supporting accurate and comprehensive forecasting.
With the characteristics of complex operations and real-time monitoring requirements, energy enterprises need to approach data management systematically, according to a data management framework such as key areas: data safety and quality, metadata management, master data, modeling, storage - operation, analysis, administration, etc. The goal is to build a unified data ecosystem, effectively supporting both operations and strategic decision making.
In particular, businesses need to clearly define their data strategy before investing in technology. "Doing data is the opposite, we must determine the specific destination of data that needs to directly serve business and management goals, instead of following technology trends in a formal way," emphasized a representative of Viettel Solutions.
Applying AI to predict, maintain and optimize operational productivity
When the data is ready, AI becomes a lever to help the energy industry operate intelligently. Mr. Pham Tuong Chien, Technology Director of Viettel Cloud Platform, said that Viettel owns a series of practical applications of AI in the energy sector: from forecasting electricity load, analyzing abnormalities, proactive maintenance to automation and decision support.
Viettel is deploying field-specific AI models to analyze sensor, camera, audio, temperature data, etc. in real time. Thanks to that, the system can detect abnormalities before problems occur, automatically adjust maintenance schedules to reduce downtime and optimize operating costs.
In addition, AI also supports analyzing generator images, measuring performance, optimizing renewable energy storage, and operating technical chatbot systems in factories. These AI models are trained and operated through AI Studio, a platform that integrates tools such as Jupyter Notebook, AI inference (API), central storage, etc., helping businesses deploy AI from testing to actual products without investing in separate infrastructure.
According to experts, digital transformation in the energy industry cannot stop at the application of discrete technologies. True value is only created when data, AI, IoT and computing infrastructure are connected into a unified ecosystem – capable of expanding on demand and ensuring sovereignty in operations.
Currently, Viettel Solutions owns a "Make in Vietnam" digital ecosystem platform, specifically designed for Vietnamese businesses. This ecosystem allows the deployment of the entire AI lifecycle right on domestic cloud computing infrastructure, from flexible hourly GPU-as-a-Service services, to the Kubernetes (VKE) orchestration platform, and AI Studio for model development, training, and inference.
Businesses can easily put AI models into practice without investing in physical infrastructure, while still ensuring speed, security and smooth integration with existing operating systems such as EMS, HMI...
In the journey of digital transformation in the energy industry, the combination of data and AI not only helps Vietnamese businesses optimize operations, but also empowers them to proactively shape the future of technology instead of depending on international solutions.
Hien Minh
Source: https://baochinhphu.vn/du-lieu-va-ai-dang-tro-thanh-nguon-dien-thu-second-cho-nganh-nang-luong-10225073015562302.htm
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