Answers are grounded in this paper and cite their sources.
Analysis reveals enhanced inventory control and customer behavior insights in retail systems, suggesting improved decision-making.
In the rapid development of information technology, using enterprise data to support timely management decisions is crucial in helping businesses operate effectively and improve competitiveness. This study uses Microsoft power business intelligence (MPBI) to analyze data in retail systems, allowing managers to grasp the business situation in real time, track advanced sales, optimize inventory control, and analyze customer behavior and supply chain visibility. From the data generated by the business, the study uses the streaming extract transform load (ETL) model to support real-time data aggregation, then converts to the MPBI data visualization system to convert data into visual charts, helping businesses easily monitor, track, analyze, and make decisions to promote business activities. The study proposes a data structure to organize retail information storage. It proposes a system of calculation formulas and data synthesis, making integrate and convert tabular data into visual charts. Through analysis of real data from the LH83 retail system, the study shows the feasibility of implementing a data visualization system and the difficulties encountered when businesses want to deploy this model.
No takes yet. Share an insight, caveat, or question.
Quoc et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: