Indispensable data platform: Enterprise Research·Social Science Big Data Platform
Qiyam·Social Science Big Data Platform (https://r.qiyamdata.com) is a new social science big data download platform carefully created by Qiyamdata for teaching and scientific research in the field of social sciences in China. Three data modules: "Co-construction of universities", "Hot Topics" and "More Data" are now open to all types of university scientific research institutions across the country.
The special database module co-constructed by universities includes enterprise research data. In order to help the country promote major strategic deployments such as rural revitalization, inclusive finance and green development, it has jointly built various academic field special databases with scientific research institutions from several well-known domestic universities. At present, the special databases that have been built and open to the public under the "Co-construction of Colleges and Universities" include Zhejiang University's Carter-Enterprise Research China Agricultural Research Database (CCAD) in the field of "agriculture, rural areas and farmers", CCAD 2023 version data introduction, and Zhejiang University's Tailong-In the field of inclusive finance . An introduction to the 2023 version of the TFID data of the Enterprise Research China Inclusive Finance Database (TFID) , and a brief introduction to the 2023 version of the China Public Policy and Green Development Database (CPPGD) in the field of green development .
Hot topics include frontier industry big data, hot regional big data, digital economy big data, technological innovation big data, common prosperity, and more data (including listed companies, transportation, humanities education, business and trade, investment activities, One Belt and One Road, administration, macroeconomics).
Enterprise Research·Database Resource Overview (2023.08)
In addition to the above data, the social science big data platform also has teaching case sharing, representative results display, scientific research knowledge, Python step-by-step teaching videos, and high-level charting tools and other small tools and knowledge to help users better use data. .
