Big Data Platform Model and its rolein Data Quality and Business Intelligence

Business intelligence contributes to decision making in intelligent business and business activities based on data storage and analysis. In this study, "Big Data Technologies" is divided into a set of infrastructures including computing, data storage, data analysis, data visualization, data automation, security, and privacy. The challenges of poor data quality are divided into two categories of internal and external challenges. The inadequacy of internal data challenges are related to the readiness level of business and organizational culture, and the deployment of a big data platform will impact the organization's readiness and culture. In the proposed big data platform, considering each of the two factors, acquisition of business data domains and business readiness assessment, software and hardware is selected proportional from each of the big data technologies. To collect the model data, a researcher-made questionnaire was used and a stratified random sampling method was used. In this research, 37 business managers and experts were selected as the sample for answering the questionnaire. Data was modeled in least squares modular structural equation modeling in SmartPlus Script 3 software environment and the results showed that designing a large data platform and data quality challenges comparing to other variables have the highest impact on business intelligence. Considering the importance of performance matrix, big data platform design, big data technologies, and business acceptance measurements have the highest percentages of importance and performance in the model, respectively