| 刊名 | Meteorological and Environmental Research |
| 作者 | Zhuoran LI* |
| 作者单位 | Q-Square Business Intelligence, Corp., Tianjin 300000, China |
| DOI | 10.19547/j.issn2152-3940.2026.01.008 |
| 年份 | 2026 |
| 刊期 | 1 |
| 页码 | 45~47 |
| 关键词 | Big data; Statistical analysis; Current status; Development prospects |
| 摘要 | With the advent of the big data era, modern statistics has enjoyed unprecedented development opportunities and also faced numerous new challenges. Traditional statistical computing methods are often limited by issues such as computer memory capacity and distributed storage of data across different locations, and are unable to directly apply to large-scale data sets. Therefore, in the context of big data, designing efficient and theoretically guaranteed statistical learning and inference algorithms has become a key issue that the current field of statistics urgently needs to address. In this paper, the application status of statistical analysis methods in the big data environment was systematically reviewed, and its future development directions were analyzed to provide reference and support for the further development of theory and methods of the statistical analysis of big data. |
