Editor's note
In the beginning of 2021, APAC CIO Outlook, a professional media in Silicon Valley in the United States, specially planned industry technology trends and invited industry leaders to share their views on technology development trends in the fields of big data and cloud computing. Dr. Liu Yijing, CTO of Baifen Technology, was invited to publish a signed article "Five Trends in the Application of Data Intelligence Technology in the Next 3-5 Years".
Companies around the world are accelerating their digital and intelligent transformations, and increasingly focus their IT strategies on business intelligence, prompting CIOs to move to the foreground, timely finding out the shortcomings in their business processes and operations, and adopting digital Top-level design and IT technology to solve problems. We believe that in the next 3-5 years, the application of data intelligence technology will present five major trends:
First, the integration of data, technology and scenarios.
In the process of digital and intelligent transformation, enterprises need to use a new generation of information technology to optimize business processes, analyze business problems, gain insights into business trends, assist business decisions, and ultimately bring actions. This is a complex closed-loop scenario. At the same time, the complexity of applications has led to the complexity of data requirements. Business data, log data (machine data), IoT data (sensor data), annotation data (artificial experience), simulation data, and knowledge data must be combined and used. In order to effectively achieve the goals of digital transformation and intelligent transformation.
It can be seen that this trend is driven by applications. Moreover, integration is not only reflected in the integration of multiple data, but also in the integration of multiple technologies and multiple application scenarios. It is necessary to integrate upstream and downstream technologies, involving IoT, edge computing, cloud, privacy protection, big data, and business intelligence. , Artificial intelligence and AR/VR/MR and a series of technologies.
Second, applications will increasingly emphasize real-time.
With the acceleration of digital transformation, more and more application scenarios require timely or even immediate response, from the previous T+1 to T+0, which places high demands on infrastructure and data technology.
Therefore, real-time is the general trend of data intelligent applications in the future. As real-time requirements are getting higher and the amount of data processing is increasing, real-time computing-related technologies will become more and more popular. In the future, Spark, Streaming, Flink and other technologies will be more and more widely used, and even replace Hadoop, MapReduce and other technologies.
Third, the interactive AI is comprehensive.
At present, self-service customer service has gradually replaced people's repetitive labor, and the answer people want can be quickly answered by the way of machine question and answer. It is conceivable that when data intelligence technology is gradually applied to various fields, even non-professionals should be able to apply data intelligence to assist decision-making.
However, to make the interaction between humans and machines, between people and organizations, and between organizations and organizations more and more natural, flexible and efficient, this requires technology to creatively overcome time, space, language, and even vision, hearing, and Sensory obstacles such as touch and smell.
Fourth, machine automation and autonomy.
Compared with the previous data intelligence technology, which can only perform precisely defined tasks, disinfection robots, dispensing robots, and food delivery robots are now more and more used, and they have a certain degree of autonomy in specific task areas and routes.
In fact, AI in essence is to continuously summarize the laws. As more and more data deposits, machines have shown a trend of autonomous evolution, helping people make more choices and judgments. In addition, autonomy is also reflected in that the system can carry out certain tasks in the closed loop of perception, cognition, decision-making and action by itself after being appropriately authorized.
Fifth, edge computing empowers data privacy protection.
Data security and privacy issues are issues that still need to be resolved in the next 3-5 years. In the past, the traditional way was to aggregate data to the cloud for centralized processing, analysis, modeling, and application. With the enhancement of edge nodes and equipment capabilities, companies will run different predictive analysis and AI models at the edge, enabling more operations to be performed on terminals or edge nodes without uploading private data.
About APAC CIOOutlook:
APAC CIO Outlook is a monthly magazine published by Silicon Valley in the United States, focusing on sharing corporate IT experience, wisdom and advice to CXO groups. It is known as the top media "radiating 180,000 Asia-Pacific English readers". Aiming at leading technology trends such as cloud computing, big data, mobile computing, and security in the enterprise application field, delivering practical and actionable first-hand to CEOs, CIOs, CTOs, VCs, and other high-level IT buyers and decision makers News.