Developing Integrated Performance Dashboards Visualisations Using Power BI as a Platform

Abstract

The rapid advance of business technologies in recent years has made knowledge an essential and strategic asset that determines the success or failure of an organisation. Access to the right information in real time and with high selectivity can be a competitive advantage in the business environment. Business intelligence systems help corporate executives, business managers, and other operational workers make better and more informed business decisions. This study aimed to assess the impact of using business intelligence tools on the decision-making process in organisations, specifically in sales marketing. The methodology applied to realise the study’s objective was the Vercellis methodology. A set of data available on the sales marketing website SuperDataScience was used to implement a set of pressing KPIs for the business decision-making process in the area. Using these data, a complete business intelligence system solution was implemented. A data warehouse was created using the ETL (extract–transform–load) process, and the data were then explored using a set of dynamics dashboards with a view of the business metrics. The results showed the use of business intelligence systems that allow the integration and transformation of data from various sources stored in data warehouses, where it is possible to implement KPIs and carry out quick, concise, easy-to-interpret graphical analyses. This paper contributes to a better understanding of the importance of data-integrated dashboard visualisation for the decision-making process.

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

“…Its main emphasis lies in the control of the monitoring activities of the screening station. The digital dashboard contains a suite of functionality such as real-time monitoring [47,48], Overall Equipment Effectiveness (OEE) [49], and graphical analytics that depict the historical trends and patterns of the screening station. The entire package of these features allows for a complete picture of the station functioning, as well as more effective decision-making.…”

“…The new system will be based on an ML model that uses its history data from the station [50]. The forecasting function gives a chance to view the estimated output and device operation effectiveness and hence enable our production management [47,48,51].…”