The primary goal of the final thesis was to centralize sales operations and design a fully automated ecosystem covering the complete customer lifecycle—from initial lead capture to project delivery and invoicing—while providing real-time analytical insights for decision-makers.

Objectives:

• Automate data transitions between Lead, Opportunity, Project, and Invoice stages.

• Eliminate manual data entry and fragmented data sources.

• Integrate operational CRM data with advanced business intelligence.

• Embed analytics directly into the CRM user interface.

Technologies and Techniques Used:

• Microsoft Dataverse as the core relational database with custom entities and business logic.

• Model-driven Power App for an efficient, process-oriented user interface.

• Power Automate with 6 dedicated workflows for process orchestration, approvals, budget control, and invoicing.

• Power BI & Power BI Dataflows for cloud-based ETL, data transformation, and advanced analytics.

• Embedded Power BI (HTML Web Resource) for seamless analytics within the CRM environment.

Results:

• A fully integrated end-to-end CRM and analytics solution providing a 360-degree view of sales, projects, and financial performance.

• Significant reduction of administrative workload through automation and standardized workflows.

• Real-time dashboards presenting KPIs, conversion rates, project health, profitability, and revenue trends.

• Built-in proactive risk management through automated alerts at critical project thresholds.

• A scalable, enterprise-ready solution designed for future enhancements such as AI-driven forecasting and customer portals.