Software development tools, such as issue tracking system (ITS) and version control system (VCS), are widely used in the intelligent development of open source software and commercial software. When using these tools to assist software development, they produce substantial amount of data, which is called software development activity data. Data quality has attracted more and more attention with increasingly rich software activity data sources and their wide uses. Faithfully, data is the basis of intelligent development. Data quality has influence on research and practice. To remind data users of latent data quality problem of software developement activity data, three aspects are indicated that may have data quality problems through literature review and interview with data users. The data quality problems arose from three phases, i.e., data production, data collection, and data use. Next, to improve the data quality of software development activity data, several recommendations are proposed that could be taken into consideration, including finding data quality problems and solving data quality problems. First of all, researchers should have a clear understanding of the context of data. Next, they may use statistical analysis and data visualization to find latent data quality problems. Finally, they can try to correct the particular problems by redundant data or to improve data quality by user behavior analysis.