欢乐生肖

New Energy Data Administration

Strong Support for
New Energy Data Governance in the Times of Big Data

Through the approaches of standardization, quality inspection, analysis, diagnosis, cleaning, integration, and monitoring, it solves the problem of dispersion, diversification, poor quality, low utilization, irregular management of data for power grids, the group and owners of power plants. It improves data management and creates new energy data control and administration system for the customers, so as to ensure the stability of data administration in the companies. It exploits the application value of data and takes advantage of information technology of big data to improve the planning ability of power grids, the management of groups, and data quality of power plants.

欢乐生肖Standardization of Data

Data Mining

Data Processing with Information Technology

Administration System

Key Targets of Data Management

Ensure the normal operation of the core business, enhance the value of data, and exploit the application value of data.

Data Standard System

Analyze the workflow of business, design the master data index of business, and create data standard specification.

Check and Improve data Quality, and Monitor Data of Key Importance

Check, solve, and handle the problem of data quality to enhance the value of data.

Data Integration Sharing

Various kinds of processed high-quality production data are stored in a centralized way that facilitates their retrieve, application, and sharing, and supports application integration of data.

Data Control System

Develop a comprehensive data management system where data can be produced, processed, monitored, retrieved, used, and shared, and make data management an everyday routine.

Data Quality Administration Platform

Provide customers with comprehensive data management solutions, ensure business operation, enhance data value and assist management decision。

Key Advantages

Real-time Monitoring

Ensure the accuracy and effectiveness of decision information through real-time data quality monitoring and automatic node diagnosis and data cleaning.

Quick Positioning

Find the source of erroneous data accurately and quickly and handle them in time, so as to mitigate or even prevent loss.

Unified Standard

Use unified standards of data and regulate the procedures for data administration to establish rules and regulations for data monitoring and application.

Effective Implementation

Ensure effective implementation of the data control system through performance assessment。

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