R&D Quality Management Of Data Governance Software Of X Company

With the continuous progress and development of science and technology in China,the number of software engineering is increasing.If software engineering is really carried out,the quality management of product development is very important.In order to promote the healthy development of software engineering,the problems existing in the research and development process should be analyzed and solved.The data governance software products launched by X Company are used to assist big data integration,intelligent analysis and other data governance businesses in the digital transformation of enterprises.After the V1.0 version went online,we won the bid for an enterprise data governance project.During the implementation process,the product quality problems were obvious,and customers reported many problems.After the project acceptance is passed,the existing problems will be reviewed.It is planned to introduce the Dai Minghuan Quality Management Method(PDCA)in the subsequent version,and develop a scientific R&D quality improvement plan to achieve a great leap in quality.This paper combines the actual progress of the work,through the quantitative analysis of the relevant indicators that affect the quality of research and development,adopts targeted measures to correct according to the degree of impact,integrates theory in practice,and forms a quality solution for the research and development process.The main research contents include the following:1.In view of the contradictions existing in the data governance software development process of different enterprises,we explored the software application scenarios of X Company,combined with the company’s internal organizational structure,and studied the exposed quality problems according to the management,spot check,traceability and other links.We identified four important issues affecting quality,including: imprecise R&D assessment management,frequent demand changes,non-standard R&D testing process,and lax quality assurance process.2.Use the analytic hierarchy process(AHP)algorithm to conduct quantitative research on the relevant indicators of four quality problems,establish a structural model,and obtain the weight ranking of indicators through the judgment matrix and consistency test calculation.The results show that the four indicators of demand baseline,change process,performance indicators,and defect rate have the greatest impact on the quality management of data governance software.3.According to the calculated weight results,the four quality problems are decomposed in four stages: planning stage,implementation stage,inspection stage,and treatment stage.The root causes of the problems are found in different links,the main influencing factors are implemented,the scope and depth of the impact of the problem are defined,and the PDCA model for problem treatment is formed.4.After the quality improvement of the product,we collected data for quantitative analysis by entropy method,and combined with market feedback for qualitative analysis.The results show that the quality of the software has significantly improved.The problem solving model studied in this paper has been used iteratively through different versions of the product,and the application effect has reached the expectation.A long-term mechanism of high quality management has been established in four aspects,namely,system,training,configuration and organization.