How to understand the challenges and opportunities faced by statistics under the background of big data?

1. The challenge of big data to statistics

Traditional statistics generally stay in sampling technology to collect data from the crowd, and then establish a model to analyze the data statistically. However, with so much data today, traditional statistics is facing great challenges in this respect. If statistics want to bring forth the old and bring forth the new, it must reform itself.

2. Opportunities brought by big data to statistics

Statistics has always been a subject of studying data. Statistics and big data are intrinsically linked. Big data makes statistics a dominant discipline, and now many teaching units attach great importance to the cultivation of statistical talents. Statistics can make people better grasp the analysis and application of data. Summarized the following development opportunities brought by the era of big data to statistics.

(1) Big data provides a new research direction for statistics, and the analysis of big data provides new practical value for statistics, because not only e-commerce and traditional commerce, but also the government needs to analyze complex data to find out macro and micro information about economic development trends, public preferences and needs. In order to obtain this information, statistical research will introduce more rigorous and systematic scientific methods.

(2) Statistics can make full use of the development of computer technology, statistical theories and methods need to gain new vitality in interdisciplinary subjects, and statistics should seek inspiration for statistical development from the current data development trend. Considering the development of information technology, cloud computing and Internet, the government statistics is the basis of modern statistics, and it has developed from traditional statistics to modern statistics.

(3) New requirements are put forward for the training of statistical talents. What is needed now is not only statistical talents who have a clear understanding of statistical theory knowledge, but also high-level data analysts, who are compound talents with mathematical knowledge, statistical modeling knowledge, computer skills, programming skills, big data mining and management skills.

(4) The statistical theoretical model can be further deepened. The current statistical analysis is different from the past, and the acquisition of statistical indicators has to go through a complicated calculus process. Now generally rely on large software programs, but these large soft

However, the compilation of software programs needs a specific statistical model to complete. In order to get the priority of development in the era of big data, we must develop the corresponding mathematical statistical model.