七月数据交易市场热度回升 产品结构优化显著

Core Insights - The data trading market has shown signs of recovery in July, with a total of 315 data products launched by seven data trading institutions, reflecting enhanced competitiveness and standardized construction of data trading platforms [3][4] - The "element density" score increased significantly by 14.25% from 3.72 to 4.25, indicating a shift towards a more diverse and complete product system driven by data [3][4] - The "application potential" score decreased by 2.62%, highlighting the need for data trading institutions to improve product lifecycle management and update efficiency [4] Element Density - The "element density" scores of various data trading institutions have generally maintained high levels, with Zhengzhou Data Trading Center showing a remarkable increase of 62.9% in "data participation" score from 2.25 to 3.67, indicating a focus on structured data resources [8] - Guangzhou Data Trading Center's score in "data integration" rose significantly from 3.79 to 5.00, reflecting improvements in data type and comprehensiveness [8] Transparency - The scores for "basic information disclosure" and "price transparency" showed significant divergence, with Zhengzhou Data Trading Center achieving a score of 3.00, a 200% increase from June [10] - Overall, the "price transparency" scores remained low, ranging from 1.00 to 2.06, indicating shortcomings in pricing logic and comparison mechanisms in the data trading market [10] Stability Coefficient - The "stability coefficient" dimension showed varied performance, with Zhengzhou Data Trading Center nearing full marks in "data grading," indicating strong governance in data classification [13] - Shanghai Data Exchange, Beijing International Data Exchange, and Guangzhou Data Trading Center led in "data source" scores, reflecting high compliance in data collection and original data tracing [13] Application Potential - The "application potential" scores are composed of update frequency, attention, and reusability, with attention scores generally high, indicating active market exposure [16] - However, the update frequency scores were notably low, suggesting that the current product iteration mechanisms are inadequate, which may hinder the vitality of data product lifecycles [16]