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Throughout history, significant technological developments have transformed productivity and our day-to-day lives, ushering society from age to age. The most obvious example is the evolution of tools, and how they have shaped our world, from the agricultural revolution in the Stone Age to the Industrial Revolution powered by steam engines and electrification. Now, the digital and intelligent transformations of the 20th century are guiding us into the digital-intelligent age.
What sets the digital-intelligent age apart is its creation of a digital world. Previously, increased productivity reshaped the physical world, but in the digital-intelligent age, processing information digitally has led to the creation of an entirely new digital realm, which in turn, enhances our ability to transform the physical world. Thanks to digital tools, tasks that were once impossible or very challenging—such as solving complex equations, precisely forecasting the weather, or processing real-time financial transactions—have not only become possible but also very practical.
In this age, transformations are a two-phase process: first, there is an analog transformation in the digital world, and it is followed by an actual transformation in the physical world. There are examples of this in many sectors, including the ability to precisely and quickly locate reservoirs through mass data analysis and the ability to manage power plant workloads and optimize grid distribution through large-scale data processing to prevent faults and minimize waste.
Data is the bridge between the physical and digital worlds. It captures and transmits patterns from the physical work, and these patterns become clearer as the volume and quality of data increase. Better data enables us to create more accurate simulations, which in turn result in more successful physical-world transformations.
The digital world is built on digitalization and intelligence. Digitalization is the foundation that supports the evolution of intelligence.
Digitalization enables us to store and transmit real-world information in digital formats. This accelerates information processing and generates vast quantities of data that can be used for intelligent learning and training. The conversion from information to knowledge allows us to use this data to fuel the development of AI. As AI technologies are deployed across industries, they further increase digitalization, thus driving a continuous cycle of growth. This cycle creates an ever-increasing volume of high-quality data that, in turn, powers intelligence.
Data is the critical link between digitalization and intelligence. It accelerates both and enables a symbiotic relationship to arise between them. As digital transformation deepens and intelligence evolves, the boundaries between the two begin to blur, creating a unified digital-intelligent force. This convergence results in explosive data growth, as digitalization reaches new levels and AI breakthroughs unlock immense potential to create value. The end result is a surge of energy that drives productivity transformations across industries.
Data infrastructure serves as the backbone of the digital world, and it provides the physical foundation for all digital transformations. As data volumes and their value continue to grow exponentially, future-proof data storage power is becoming essential for maintaining a resilient, high-performance digital ecosystem.
Data storage power refers to comprehensive storage capabilities including performance, reliability, and environmental impact.
Future-proof data storage power leverages data infrastructure to process and manage ever-increasing volumes of data scale in the digital-intelligent era. It is centered on storage capacity and built around six core pillars: ultimate performance, flexible scalability, strong resilience, simplified paradigm, easy management, and sustainable development.
• Ultimate Performance
Intelligent transformation is driving further digitalization and giving rise to larger volumes of data. As a result, stronger data processing capabilities are needed to provide faster data access, boost the efficiency of digital service processing, and improve the computing power utilization and inference throughput of large AI models. Data infrastructure needs to offer hundreds of millions of IOPS and hundreds of TB/s of bandwidth to deliver sufficient performance in the digital-intelligent era.
• Flexible Scalability
It has been suggested that the global data volume doubles every two years on average and will reach the yottabyte level by around 2030. Future-proof data storage power needs to be able to keep up with demand for online EB-level scalability.
• Strong Resilience
Disaster recovery and backup were the main concerns when it came to data resilience. At the moment, there is a ransomware attack every 11 seconds on average. The widespread deployment of intelligent applications will also increase the incidence of ransomware attacks. By around 2030, ransomware attacks are expected to occur every 2 seconds on average. Therefore, to prevent ransomware attacks before they can cause damage, all data owners must ensure that their data is well protected by a comprehensive and resilient system that includes data disaster recovery, backup, and ransomware protection.
• Simplified Paradigm
The evolution of data infrastructure shows that the data paradigm has evolved from block-based structured data to file-based unstructured data, and finally to object-based mass data. Each data paradigm has emerged as a result of the ongoing changes to upper-layer services. Data paradigms like RAG vector and long-term memory storage with multi-level KV cache have emerged to support service growth in the digital-intelligent era. Future-proof data storage power must support these simplified data paradigms that arise from emerging applications.
• Easy Management
Data becomes more valuable than ever in the digital-intelligent era. It has now become an enterprise asset and the fifth factor of production following land, labor, capital, and technology. However, mass data is scattered across enterprise data centers in different regions, and this makes achieving efficient data flows challenging. Therefore, data infrastructure needs to enable easy management of mass data across multiple regions. One way of doing this would be to use a global file system, because it facilitates data search and on-demand data flows through visualized data management maps.
• Sustainable Development
Data is one of the most valuable enterprise assets. It has a lifecycle that gets continually extended. Hot data is frequently accessed over a longer period of time, and cold data becomes warm data in preparation for anytime access. Therefore, securing sustainable high-density data infrastructure that has been carefully designed to ensure energy savings and space savings without compromising service continuity must be a top priority for enterprises.
Future-proof data storage power showcases the value of data storage. It is the engine that drives the rapid development of digital productivity. In the digital-intelligent era, future-proof data storage power is a necessity. It accelerates the digital and intelligent transformations and their convergence, and enables enterprises to move towards an intelligent world.
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