Microsoft Power BI performance optimization for finance applications
Keywords:
Microsoft Power BI, finance analytics, performance optimizationAbstract
For financial professionals, Microsoft Power BI has become a necessary tool as it helps to analyze huge amounts of information, create dynamic reports & extract important insights for well-informed decisions. Still, financial applications handle huge amounts of information—including transactions, forecasts & compliance with these kinds of reports—which results in performance issues that could lead to longer-than-ideal data processing times & also report loads. Guaranteeing effective performance and accurate actual time analysis requires improving Power BI for financial applications. Common performance problems like slow DAX searches, poor data models & refresh lags—which may hinder financial reporting—are investigated in this work. It underlines the best practices to raise the efficiency of Power BI by means of data model simplification by reduction of the unnecessary columns & the connections, aggregations, query folding & DAX performance tuning techniques application. Furthermore significantly improving speed and responsiveness are methods like incremental data refresh & report graphic tuning. A case study shows how a financial services company successfully enhanced its Power BI dashboards, reducing report refresh time from minutes to seconds & maintaining data integrity. By means of these optimization techniques, financial teams might maximize the features of Power BI, thereby guaranteeing effective performance, fast decision-making & a better user experience. Improving Power BI has moved from a technical need to a strategic imperative for companies trying to maintain the agility & efficiency in a data-driven world as financial data becomes more complicated.
Downloads
References
Widjaja, Surlisa, and Tuga Mauritsius. "The development of performance dashboard visualization with power BI as platform." International Journal of Mechanical Engineering and Technology (IJMET) 10.5 (2019): 235-249.
Ferrari, Alberto, and Marco Russo. The definitive guide to DAX: Business intelligence with Microsoft Excel, SQL server analysis services, and Power BI. Microsoft Press, 2015.
Powell, Brett. Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence. Packt Publishing Ltd, 2018.
Pukala, Ryszard, et al. "Power BI in ICT for monitoring of insurance activity based on indicators of insurance portfolios." 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T). IEEE, 2020.
Kupunarapu, Sujith Kumar. "AI-Driven Crew Scheduling and Workforce Management for Improved Railroad Efficiency." International Journal of Science And Engineering 8.3 (2022): 30-37.
O'Connor, Errin. Microsoft Power BI Dashboards Step by Step. Microsoft Press, 2018.
Knight, Devin, et al. Microsoft Power BI quick start guide: Build dashboards and visualizations to make your data come to life. Packt Publishing Ltd, 2018.
Powell, Brett. Microsoft Power BI cookbook: Creating business intelligence solutions of analytical data models, reports, and dashboards. Packt Publishing Ltd, 2017.
Quintero, Dino, et al. Workload optimized systems: Tuning POWER7 for analytics. IBM Redbooks, 2013.
Yasodhara Varma. “Graph-Based Machine Learning for Credit Card Fraud Detection: A Real-World Implementation”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 2, June 2022, pp. 239-63
LeBlanc, Patrick, et al. Applied Microsoft business intelligence. John Wiley & Sons, 2015.
Atluri, Anusha. “The Autonomous HR Department: Oracle HCM’s Cutting-Edge Automation Capabilities”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 3, no. 1, Mar. 2022, pp. 47-54
Reddy, Chavva Subba, Ravi Sankar Sangam, and B. Srinivasa Rao. "A survey on business intelligence tools for marketing, financial, and transportation services." Smart Intelligent Computing and Applications: Proceedings of the Second International Conference on SCI 2018, Volume 2. Springer Singapore, 2019.
Syed, Ali Asghar Mehdi. “Networking Automation With Ansible and AI: How Automation Can Enhance Network Security and Efficiency”. Los Angeles Journal of Intelligent Systems and Pattern Recognition, vol. 3, Apr. 2023, pp. 286-0
Oey, Elia, Samuel Samudera Susjanto Harno, and Carolyn Zain. "Developing integrated performance dashboards with Power BI–a case study in a medium-size Manufacturer." 2021 International Conference on Information Management and Technology (ICIMTech). Vol. 1. IEEE, 2021.
Syed, Ali Asghar Mehdi, and Shujat Ali. “Multi-Tenancy and Security in Salesforce: Addressing Challenges and Solutions for Enterprise-Level Salesforce Integrations”. Newark Journal of Human-Centric AI and Robotics Interaction, vol. 3, Feb. 2023, pp. 356-7
Deckler, Greg. Learn Power BI: A beginner's guide to developing interactive business intelligence solutions using Microsoft Power BI. Packt Publishing Ltd, 2019.
Vasanta Kumar Tarra, and Arun Kumar Mittapelly. “AI-Driven Fraud Detection in Salesforce CRM: How ML Algorithms Can Detect Fraudulent Activities in Customer Transactions and Interactions”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 2, Oct. 2022, pp. 264-85
Knight, Devin, et al. Microsoft Power BI Complete Reference: Bring your data to life with the powerful features of Microsoft Power BI. Packt Publishing Ltd, 2018.
Atluri, Anusha, and Vijay Reddy. “Total Rewards Transformation: Exploring Oracle HCM’s Next-Level Compensation Modules”. International Journal of Emerging Research in Engineering and Technology, vol. 4, no. 1, Mar. 2023, pp. 45-53
Valdez, Alicia, et al. "Development and implementation of the balanced scorecard for a higher educational institution using business intelligence tools." International Journal of Advanced Computer Science and Applications 8.10 (2017).
Aspin, Adam. High Impact Data Visualization with Power View, Power Map, and Power BI. Apress, 2014.
