In 2018, with the maturity of big data, artificial intelligence, cloud computing, etc., we will usher in a powerful transformation, in which big data is a key area that China and the world want to force. At the same time, As a pioneer, Ring Technology has proposed the development trend of the concept technology conforming to Big Data 3.0 in advance. In addition, it has released Transwarp Data Cloud (TDC), the Star Data Big Data Cloud Platform, which realizes Big Data + Cloud + Artificial Intelligence. Fusion between the two.
At present, big data is expanding from the retail, finance, telecommunications, logistics, medical, transportation and other fields to the industrial sector. For example, a large civil airliner will generate 10 TB of data every 30 minutes; many industrial companies start to take advantage of Data analysis technology provides decision support for intelligent engineering machinery. It can be said that big data will create value in all aspects of industry, and this trend also indicates that big data is entering the 3.0 era, big data technology, artificial intelligence technology, cloud computing. Technology begins to merge. In the same platform, more industries and fields can be applied to meet more different levels of data requirements. Sun Yuanhao, founder and CEO of Xinghuan Technology, said that in the era of Big Data 3.0, the big data platform will It has three characteristics: Full data-level coverage, and the advantages of Xinghuan's products in the full data volume will be further highlighted; unified programming language, SQL regression big data, as a standard structured query language, greatly Reduce the platform's requirements for developers; one-stop convergence platform, implement cloud layer deployment and unified data platform at the hardware layer, and enhance the set
Big Data 3.0 combines the features of the previous 1.0 and 2.0 eras to become a more comprehensive platform. The data is also uninterrupted, diverse, real-time, and industry-oriented. Therefore, in the digital utilization process, The data is also more complicated. At the same time, Big Data 3.0 can bring about an industrial change. More companies will pay attention to and use their own data assets, so the application of the value chain of big data is imperative. Sun Yuanhao also believes that when Big Data 3.0 is fully popularized, ordinary people will be able to use this technology directly. By then, Big Data + Cloud + AI will be fully integrated, creating a new era of technology.
It is reported that in the industrial field, the first field of big data 3.0 is that industrial technology development has solved more business needs. The transformation and upgrading of manufacturing driven by big data is to improve production efficiency, improve product quality and save the whole industry in the future. Resource consumption, ensuring production safety, and optimizing the sales service. Through the coordinated development of technologies such as artificial intelligence and cloud computing, industrial big data will be deeply integrated into the real economy and become a new engine in the digital economy era. In these aspects, the layout is also advanced. At present, several successful examples show that this trend will be unstoppable.
One of the more successful cases is the Ningbo Wind Power Project, which is provided by Xinghuan Technology and implemented by Huafeng Data. Xinghuan Technology uses big data to help Ningbo Wind Power realize the industrial Internet, and Ningbo Wind Power uses big data technology to build a monitoring and integration platform. The flow processing technology timely grasps the real-time data of each intelligent fan, improves the overall operation management level, and realizes the landing of the industrial Internet in wind power.
Wind energy has a high degree of random volatility and intermittentness. Therefore, large-scale wind power access will bring many severe challenges to power supply and demand balance, power system security and power quality. This requires wind power enterprises to grasp the real-time data of each intelligent wind turbine in time. And the situation, so that it can be quickly adjusted and overhauled.
The geographical location of Ningbo wind power is scattered, the wind farm is located in remote mountainous areas, the basic living conditions are poor, and the management span is wide and difficult. With the development of network communication technology, software application technology and remote control technology, daily operation monitoring management has become an inevitable in Ningbo. The choice. Faced with the massive data generated by the high wind turbines in the wind farm, and the need for real-time information on the wind turbines, a wind power big data central control center was established in Ningbo to realize the accurate, real-time and unified wind turbines. Information collection; realize centralized monitoring and control and unified scheduling in remote areas, reduce management costs; realize real-time alarms, diagnose faults online, timely handle faults, reduce loss of power generation; realize massive data storage, optimize wind turbine operation, and improve performance Data support; combined with big data to achieve mobile office, providing the company with a full range of locations, time online operations and monitoring to improve the company's overall management efficiency and operational efficiency.
At the data level, big data components are an important part of the company's unified big data integrated service architecture system in the future, with emphasis on data management and data analysis. The big data management components are expanded on the existing foundation, and the enterprise is multi-sourced. The high-performance integration of massive data, storage and computing provide support; the big data analysis component provides technical supplement for the decision analysis platform, and supports the upper-level enterprise auxiliary decision-making and operational monitoring.
In the later stage, data mining and modeling of wind turbine data stored in big data platform is needed. The platform needs to support statistical analysis and mining using common language, and run in distributed computing framework, using the statistical analysis library rich in common language R and A rich graphical visualization method to analyze the data stored in Hadoop. The user can analyze the data read from HDFS through the common language R, and the SQL query returns the result data. Overall, big data is reflected in the project.
China is currently at the beginning of a huge wave. In the coming era, Big Data 3.0 will play an extremely important role. Let us wait and see.
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