Abstract:
In today's business landscape, the increase of data presents both challenges and opportunities for financial planning within companies. Access to extensive datasets offers the potential for informed decision-making, predictive insights, and enhanced efficiency. Leveraging data effectively is crucial for businesses to adapt to market changes, innovate, and manage risks. In essence, in this data-rich environment, utilizing data for financial planning is essential for a company's success and resilience in a dynamic marketplace.
This thesis serves as a comprehensive exploration of the intersection between business intelligence (BI) and artificial intelligence (AI), illuminating their integration to enhance financial planning processes within organizations. Employing a specific company's financial data as a case study, this research aims to provide a tangible demonstration of how the synergy between BI and AI can revolutionize financial planning methodologies. By delving into the intricacies of this integration, the goal is to develop a cutting-edge and sophisticated approach to crafting financial plans that not
only meet immediate objectives but also pave the way for long-term strategic success within the organization.
Utilizing a diverse array of tools such as Microsoft Power BI, Python, and R, coupled with advanced statistical models and artificial intelligence techniques, this research endeavors to evolve financial planning methodologies within companies. Through the integration of predictive analytics, the thesis seeks to enhance the accuracy and efficacy of financial forecasts, enabling the generation of actionable insights and timely alerts for potential risks and opportunities.
In summary, this thesis delves into the synergy between traditional financial planning practices and cutting-edge AI technologies, with the ultimate objective of empowering businesses to navigate complex economic landscapes with confidence and foresight.
