With the vigorous development of digital technologies such as big data, Internet of Things, artificial intelligence, and 5G, the integration of the energy and chemical industry and emerging technologies is also accelerating, promoting the accelerated evolution of intelligence, grid, and informatization. In the unstable external environment, digital transformation has become the key to the sustainable development of energy and chemical enterprises.
On December 14, the "EDT2023 China Energy and Chemical Industry Digital Technology Summit" hosted by Chenzhe Culture was held in Beijing, and the summit invited 300+ senior leaders and excellent information solution providers from information technology, information security, risk management and other related departments in the energy and chemical industry to share many excellent practices of digital transformation for energy and chemical enterprises, and comprehensively introduced various subdivision scenarios and high-quality emerging technologies in the energy and chemical industry.
It is worth mentioning that Tao Jianhui, founder & core developer of TDENGINE, was also invited to attend the summit and gave a speech on the theme of "Quickly Building an Industrial Data Processing Platform Without Upfront Investment". He pointed out that there are many problems in the existing industrial data processing software, such as system closure, lack of horizontal expansion ability, high cost is difficult to estimate, and data cleaning, transformation and aggregation are difficult. For energy and chemical companies, to further achieve digital transformation, they need to transform their data architecture to overcome these challenges. He took the high-performance, distributed Internet of Things and industrial big data platform TDengine as an example to introduce the capabilities of the new generation of industrial data processing software to the audience, and shared the results of energy companies in transforming data architectures in practical applications. Through TDengine, energy and chemical companies can quickly build an industrial data processing platform without upfront investment, and achieve efficient data cleaning, transformation, and aggregation to support complex data analysis and decision-making needs.
By integrating and optimizing data architectures, energy and chemical companies can better cope with the challenges of digital transformation and achieve greater cost reduction and efficiency increase. This is reflected in Shanghai Electric's "SmartOps Energy Storage Intelligent Operation and Maintenance System" project, which uses InfluxDB to execute queries after a week, and the memory usage reaches 80%, and there is no result after 10 minutes, which is completely unsuitable for business useAfter using TDengine for almost 1 month, using the same SQL statement, the query only needs 0.2 seconds, very good. The compression effect is also significant, and the amount of compressed data tdengine is 1 3 of influxdb when the number of acquisition points is the same.
In addition to the speeches, many participants also stopped to understand and communicate with the on-site staff in front of the booth set up by the organizer of the conference for TDengine, and had an in-depth understanding of TDENGINE's advantages and application cases in the field of industrial data processing. Let's take a look at the lively atmosphere of the scene