International Journal of Science, Engineering and TechnologyAuthors: Maria D’Souza
Abstract: The evolution of business intelligence (BI) has shifted organizations from static reporting to interactive, self-service analytics, enabling data-driven decision-making at all levels. QlikView and Qlik Sense, as leading BI platforms, leverage in-memory associative engines, advanced data modeling, and interactive dashboards to deliver rapid insights across diverse datasets. This review explores comprehensive strategies for mastering Qlik BI, focusing on data visualization, advanced analysis techniques, performance optimization, and best practices for dashboard design. It examines the architectural principles of Qlik platforms, including efficient ETL processes, schema selection, and handling of synthetic keys and circular references, which are critical for maintaining high responsiveness. The article further discusses advanced analytical capabilities such as set analysis, predictive modeling, and AI-assisted insights, demonstrating how these features enhance decision-making in industries including finance, healthcare, retail, and supply chain. Challenges such as data quality, user adoption, and scalability are identified, alongside mitigation strategies involving governance, scripting best practices, and server tuning. Future trends, including cloud and hybrid deployments, real-time streaming, augmented analytics, and mobile BI, are also considered, emphasizing their impact on the next generation of intelligent dashboards. By consolidating these insights, the review provides BI developers, analysts, and enterprise decision-makers with a practical framework for optimizing Qlik BI implementations, ensuring actionable, reliable, and high-performance dashboards that drive organizational efficiency and strategic advantage.
DOI: https://doi.org/10.5281/zenodo.17278009
