Optimization of an Opportunity Pipeline Report for a Selected Company

Abstract

This thesis focuses on the optimization of an opportunity pipeline report for a European B2B software company specializing in SaaS solutions. Although the company already used an existing report, its underlying architecture required a redesign to support advanced time-based analysis and dynamic visualization of Annual Recurring Revenue (ARR) flow. The main objective was to develop a high-performance analytical solution in Microsoft Power BI that ensures transparent tracking of opportunity movement and enables dynamic point-in-time financial reconciliation, thereby supporting data-driven decision-making in sales management. The thesis is based on a theoretical analysis of dimensional modelling and opportunity management principles. The practical part involves a complex ETL process transforming raw CRM extracts into a robust Galaxy Schema suitable for production use. Key techniques include the implementation of periodic snapshot logic for reconstructing historical states, the creation of role-playing dimensions, and the design of a dynamic fiscal calendar. Advanced asymmetric valuation algorithms were developed in DAX to incorporate type-specific win probabilities and accuracy metrics. The result is a comprehensive analytical solution consisting of interactive dashboards designed according to UX best practices. The redesigned solution introduces advanced opportunity flow visualization, allowing users to compare pipeline states between any two selected points in time and identify key drivers of revenue growth or decline. By aligning advanced data processing techniques with business needs, the thesis provides a tool that ensures full transparency of the sales process and directly supports strategic decision-making based on data.