Dangers and Opportunities of Big Data Capital Growth

Big data is no longer just a product of technological development. It has become a battlefield where global capital contends for the dominance of computing power and data discourse power in the AI era.

Few segments of the economy are as hot as data centers in recent years. Fast-spreading use of AI, on top of deepening digitization of business and daily life, means eye-watering demand for data processing. Growth is attracting huge volumes of capital, and M&A is flourishing as tech giants and utility players maneuver for dominance.

“There has been a tremendous increase in the demand for data center capacity, driven by cloud services, social networking and a range of both consumer and enterprise digital services. There is no end in sight to this trend, with generative AI technology and services adding a further boost to already strong demand,” said John Dinsdale, Chief Analyst at Synergy Research Group. “Specialist data center operators have either not been able or were not prepared to fund those investments themselves, while private equity investors have been more than willing to step in and fund growth initiatives. Looking at pending deals and the future pipeline, there is plenty of evidence to suggest that 2025 will be another boom year for data center M&A.”

The M&A boom in big data is driven by distinct capital logics across regions. In the U.S., the focus is on platform consolidation and securing data sovereignty. In China, it's about technological independence and industrial scale-up. Underneath it all is a broader race for control over strategic resources—computing power, data quality, and AI training infrastructure.

The old maxim that "data is the oil of the new era" has become increasingly literal in the generative AI context. The explosive rise of ChatGPT has not only ignited the public's enthusiasm for AI but also triggered global "data anxiety" — those with access to large, high-quality datasets are increasingly seen as holding the keys to AI supremacy.

Source: Synergy Research Group

This anxiety has directly fueled the investment boom in computing power infrastructure and data processing platforms. Data centers, cloud computing, and data governance tech are now at the center of capital deployment. Global private equity giants such as KKR, Blackstone, and TPG have stepped up their activity, while technology companies have expanded their platform capabilities through mergers and acquisitions. Among the standout deals, Cisco's acquisition of Splunk is particularly shocking. The price of $28 billion not only refreshes its historical record but also indicates that data observability and security will become one of the core competitiveness in the AI era. This acquisition is the largest transaction in Cisco's history and aims to strengthen its capabilities in AI-driven data observability and security analysis.

At the same time, technology giants such as Google and Salesforce have successively taken action to lay out data security, governance, and real-time computing, and build the prototype of an AI-native data platform. Salesforce acquired the data backup and governance platform Own Co. for $1.9 billion to enhance its capabilities in data security, privacy, and compliance. Google acquired the cloud security company Wiz for $32 billion, providing data center security tools and is expected to achieve an annual revenue of $1 billion this year, becoming Google's largest acquisition in history.

In Asia-Pacific, Blackstone's nearly $16 billion acquisition of AirTrunk—a major data center platform with operations in Australia, Japan, Malaysia, Hong Kong, and Singapore—set a regional benchmark. With over 800MW of existing capacity and the land rights to expand to over 1GW, AirTrunk represents Blackstone’s largest infrastructure bet in the region.

China's big data industry is entering a capital-intensive phase. According to the data of China Research Network, the industry reached 1.57 trillion yuan in 2023—up 18% year-on-year—and is projected to surpass 3 trillion yuan by 2025.

Although the number of investment deals dropped to 83 in 2023, total funding reached 40.8 billion yuan, suggesting a move toward larger, more strategic investments in mature enterprises.

In 2024, there were 115 investment and financing events in China's data service industry, with a total investment and financing amount of 11.581 billion yuan. During the period from 2022 to 2023 the number of investment and financing events in the industry fluctuated between 50 and 60, and it increased in 2024. If this momentum holds, 2025 could see a further rise in deal flow and capital deployed.

Distribution of investment and financing rounds in China's data service industry from 2019 to 2024

Source: chinabaogao.com

Early-stage investments, or angel and Series A rounds, still dominate, indicating the market's attention to innovative start-ups.

Between 2019 and 2024, Series A rounds were the most common type of investment in China’s data service industry, with 96 recorded events. Strategic investments followed with 90, and angel rounds totaled 88. In terms of geography, Beijing saw the highest number of transactions at 399, representing 38.34% of the total. Shanghai ranked second with 171 deals (16.43%), followed by Zhejiang, Guangdong, and Jiangsu.

According to China International Capital Corporation, China’s cloud service providers (CSPs) are expected to invest nearly 400 billion yuan into data centers by 2025, a 79% year-on-year increase. With added investment from telecom operators, the sector may hit 500 billion yuan in total—and exceed 600 billion yuan by 2027. Bank of America estimates global hyperscaler capex to grow 34% in 2025, reaching $257 billion.

As of May 2025, while the overall market data has not been fully disclosed, trends from 2024 suggest that the investment and financing in big data and its related fields will continue to focus on high-growth areas such as artificial intelligence, data transactions, and integrated circuits. Early-stage investment and strategic mergers and acquisitions are expected to remain the dominant investment approaches, with the eastern coastal regions continuing to serve as key hubs for capital activity.

Amid the surge in domestic investment in the big data sector over the past year, many representative enterprises have achieved rapid development through technological innovation and strong capital backing:

️☆Zilliz specializes in unstructured data processing and is the developer of Milvus, an open-source vector database. The company is also a member of the Linux AI Foundation. Since 2017, Zilliz has obtained three rounds of financing: including the angel round of financing led by Yunqi Capital, the Series A financing of $10 million in 2018 with the participation of Morningstar Capital, etc., and the Series B financing of $43 million in 2025 led by Hillhouse Capital. These investments have supported the company’s product development and global expansion efforts.

️☆Another notable start-up is Yunqi Technology, which is committed to building the "Yunqi Lakehouse", a data platform integrating data lakes and data warehouses. Designed for high performance, low cost, and ease of deployment, the platform addresses the growing demand among enterprises for efficient data integration and processing. In 2023, Yunqi Technology successively completed two rounds of financing, raising several hundred million yuan in total.

️☆In the field of databases and basic software, Wanli Kaiyuan stands out as a homegrown enterprise with a long-term focus on database systems and the Linux operating system. It previously partnered with MySQL to establish a joint R&D center in China. In 2023, Chuangyi Information acquired a 47.73% stake in Wanli Kaiyuan and injected additional capital, further consolidating its strategic position in the database market, The move reflects broader capital dynamics driven by the push for domestic tech substitution.

️☆ByteDance has also been actively expanding its presence in big data infrastructure. It has successively acquired TerarkDB (formerly Qijian Software) , which focuses on data storage and retrieval technology, as well as the low-code platform Heipa Yun—enhancing its capabilities in both core database technology and data application development. At the same time, through its "Volcano Engine", byteDance integrates modules such as analysis, governance, and security, building an enterprise-level data service platform that connects the entire chain of data value transformation.

Summary of Financing Data of Domestic Database Manufacturers in 2024

By looking at the big data merger and acquisition paths of China and the United States, it is not difficult to find obvious differences:

Although China and the United States take different paths in mergers and acquisitions, both center their strategies around "data + computing power." In the future, the two may engage in a deeper-level game on the AI ecosystem platform. The divergence in the investment stages not only reflect the varying maturity of the data technology ecosystems but also map out different national strategies behind them: China is accelerating efforts to ensure data security and technological self-reliance in response to international tech restrictions, while the United States is accelerating the upgrading of data infrastructure through capital integration to strengthen its leading position in AI.

Many research institutions and experts have made predictions about the current trend, and the next explosive point in the big data industry will be the formation of a closed-loop platform after integrating various AI data generation methods.

The China Research Institute of Science and Technology highlighted in a 2024 report that large model technology has significantly improved the efficiency of data analysis by more than 10 times, laying the foundation for the deep integration of AI and big data. For instance, Ant Group’s "Zhenyi" model now delivers millisecond-level fraud detection with a 0.01% false alarm rate. According to the survey, 78% of enterprises have embedded AI in the data analysis process, and the penetration rate of intelligent decision-making system has jumped from 12% in 2025 to 45% in 2024, which intuitively reflects the high recognition and widespread application of AI technology by enterprises.

Li Wei, Deputy Director of the Institute of Cloud Computing and Big Data of the China Academy of Information and Communications Technology, said that the development of multimodal AI is accelerating this transformation. By integrating inputs like text, images, and audio, AI systems are becoming more intelligent and adaptive. In a fully closed-loop platform, this means data isn’t just processed once—it continuously informs and evolves with each cycle. For example, in the healthcare field, by integrating multimodal data such as patients' medical records and medical images, the AI system can conduct comprehensive analysis, which can not only improve the accuracy of disease detection, but also further optimize the diagnostic model based on feedback from treatment. This closed-loop model can greatly enhance the value of data and drive the big data industry to a new stage of development.

AI is set to maintain strong momentum in 2025, pushing the data center industry to the brink of a transformative shift. In the past few years, billions of dollars have been invested in AI, driving the demand for more powerful and efficient data center infrastructure. The "2025 Global Data Center Outlook" by JLL, an American real estate and investment company, noted that the small modular reactor (SMR) is expected to accelerate in 2025 with total power capacity potentially doubling to meet escalating energy demands. Meanwhile, liquid cooling is emerging as a critical solution to keep pace with advancing GPU technology, rapidly becoming the “norm” in new data center builds.

Source: Semi Analysis

From a Chinese market perspective, data elements are increasingly converging with AI. According to the 2024 China Data Cloud Market Research Report by CCID Consulting, five key trends are expected to shape the future of domestic data sector:

1. AI large models empowering data science – Advanced models are delivering more intelligent algorithms, enabling more accurate data analysis and prediction.

2. Greater focus on model interpretability and reliability – Techniques such as interpretable machine learning and causal inference are being adopted to make algorithmic decisions more transparent, fair, and understandable.

3. Rise of automated and self-service analytics tools – These tools lower the technical barrier, allowing non-experts to perform data analysis and build machine learning models.

4. Integration of edge computing and IoT – This convergence brings more data sources and application scenarios, supporting real-time analysis and decision-making at the edge.

5. Decoupling of data from specific applications – Data is evolving into an independent asset, no longer tied to single use cases, but able to serve a variety of business scenarios more flexibly.

Data centers continue to draw increasing capital, particularly from new entrants eyeing high-yield, opportunistic, and value-added segments of the market—sectors supported by a solid and growing foundation.

The "2024 Global Data Center Investor Intentions Survey" released by CBRE, an American real estate services firm, shows that 97% of the respondents plan to increase their capital deployment in the data center field this year. Currently, 38% of the respondents allocate less than 5% of their asset to data centers, but that figure is expected to shrink dramatically—only 8% anticipate keeping allocations below 5% within five years. Investment activity surged in the second half of 2024, with trading volumes rising across all categories, including single-asset sales, core asset refinancing, and custom-built joint ventures. The annual sales exceeded $6.5 billion, and the average sales price also increased year-on-year, reflecting the growth of the scale of data center parks. Notably, 11 asset sales exceeded $90 million, with five of those deals topping $400 million.

The capital competition between China and the United States in the big data arena has long gone beyond simple commercial games and has evolved into a contest of national strategic capabilities. From computing power infrastructure to AI-native data ecosystems, each investment move plays a role in shaping the global tech order. In this new era of digital geopolitics, the nation that builds a safer, more efficient, and more intelligent data infrastructure may well define the next phase of the AI age.