近年來,人工智能、大數據等技術的發展給情報學的發展帶來機遇。然而,情報學界的學者常將情報分析與數據分析混為一談,情報分析研究被"泛大數據化"或被弱化為數據分析研究。為避免此類問題,文章對情報分析與數據分析的關系進行辨析。通過對比分析,發現數據分析是情報分析的基礎,大數據分析是數據分析方法體系的重要組成,但是無法取代情報分析。兩者之間區別顯著:從數據對象維度來看,數據分析方法以處理單源數據為主,情報分析方法以處理關聯的全源數據為主;從產出結果來看,數據分析產出的是新信息、新知識,情報分析產出的是新智能;從分析起點維度來看,數據分析主要是數據驅動,情報分析主要是目標驅動;從分析方法維度看,數據分析以定量分析為主,定性分析、歸納推理、演繹推理為輔,情報分析在產出新信息、新知識階段以定量分析為主,在智能產出階段以歸納推理、演繹推理為主。

In recent years,the development of technologies such as artificial intelligence and big data has brought opportunities for the development of Information Science.However,scholars in the Information Science community often confuse intelligence analysis with data analysis,and intelligence analysis research has the tendency of over big data or is weakened into data analysis research.In order to avoid such problems,this paper analyzes the relationship between intelligence analysis and data analysis.Through comparative analysis,it is found that data analysis is the basis of intelligence analysis,and big data analysis is an important component of the data analysis method system,but it cannot replace intelligence analysis.The differences between intelligence analysis and data analysis are obvious.From the dimension of data object,the data analysis method focuses on processing single-source data,and the intelligence analysis method mainly deals with the related full-source data.From the perspective of output results,data analysis yields new information and new knowledge,while intelligence analysis yields new intelligence.From the dimension of the starting point of analysis,data analysis is mainly driven by data,while intelligence analysis is mainly driven by goals.From the analysis method perspective,data analysis is mainly based on quantitative analysis,and supplemented by qualitative analysis,inductive reasoning,and deductive reasoning,and intelligence analysis mainly focuses on quantitative analysis at the stage of outputting new information and new knowledge,and inductive reasoning and deductive reasoning at the intelligence output stage.