Microsoft Fabric Direct Lake Semantic Modeling on SharePoint Online Document Estates & Delta Parquet | LoveSharePoint
1. Executive Summary & Problem Analysis
Organizations maintain vast operational datasets stored within SharePoint Online Excel and CSV tables. Traditional Power BI scheduled imports induce data latency, refresh timeouts, and compute duplication. Business analysts lack real-time semantic analytics across unstructured document repositories.
An enterprise data pipeline that streams SharePoint Online document metadata and structured table records directly into Microsoft Fabric OneLake Delta Parquet tables, enabling real-time Direct Lake Power BI semantic models and automated enterprise GenAI data indexing.
In large-scale Microsoft 365 enterprise tenants spanning tens of thousands of active site collections, manual administration and ad-hoc scripting introduce severe compliance vulnerabilities, operational latency, and unexpected cloud license expenses. When security baselines and storage quotas are managed reactively, organizations encounter compounding technical debt: unmonitored version trees degrade Microsoft 365 Copilot semantic search indexing, expired application secrets halt overnight ETL workflows, and orphaned guest sharing links violate ISO 27001 and GDPR compliance frameworks.
This technical guide by LoveSharePoint Team establishes an automated, auditable engineering architecture designed to enforce governance baselines at tenant scale while minimizing administrative overhead.