Finance dashboards with SAP data and power BI: Reliable reporting patterns

Financial reporting reliability remains a persistent challenge in organizations leveraging SAP ERP data within self-service business intelligence platforms such as Power BI. While SAP systems provide structured and auditable financial records, inconsistencies often arise during data extraction, transformation, semantic modelling, and dashboard visualization. These gaps lead to reconciliation mismatches, performance inefficiencies, and governance risks that undermine executive trust. This study proposes a structured framework of Reliable Reporting Patterns designed to ensure data accuracy, consistency, auditability, and performance integrity in SAP–Power BI finance dashboards. The framework integrates controlled extraction mechanisms, reconciliation validation controls, semantic layer governance, and performance optimization strategies within a unified architecture. By aligning technical design with financial control principles, the study offers a replicable implementation blueprint for enterprise environments. The findings contribute to both academic discourse on information reliability and practical guidance for CFOs, finance teams, and data engineering leaders seeking dependable analytics ecosystems.