Centralized Reporting for Hospitality - A Microsoft Fabric and Power BI Transformation

**Objective​** The objective of this project is to design and develop an in-house Business Intelligence (BI) platform using Microsoft Fabric and Power BI to enable centralized, real-time, and standardized reporting across multiple operational systems.​ The platform aims to:​ 1\. Establish a single source of truth by consolidating data from various hotel systems into a unified reporting framework.​ 2\. Improve data-driven decision-making through real-time analytics and standardized KPIs accessible to all teams.​ 3\. Reduce reliance on external tools and manual reporting processes by automating data ingestion, transformation, and visualization.​ 4\. Integrate essential business datasets (based on prioritized data sources) including operational reports, accounting/P\&L data, and performance metrics.​ ![]() **Technology**​ **1. Power Automate** – Triggered automation , whenever client sends new email to us, Automated redirection of that document to SharePoint.​ **2. SharePoint** - Acted as the central repository where Client uploaded Excel/PDF reports that were automatically fetched by the system.​ **3. Fabric Artifact:** * **Pipelines** – Designed automated workflows to orchestrate data ingestion, transformation, and movement across Bronze, Silver, and Gold layers.​ * **Processing(Notebooks)** – Used for scalable data processing, cleaning, transformation, and normalization of raw Excel data.​ * **Lakehouse** – A structured layer built for fast reporting and analysis.​ * **Model** – A simplified view of the data that makes reporting easier.​ * **Dashboards** – Visual reports that show insights and updates in real time​ **Goals​** 1\. Automate the manual process of collecting and consolidating reports from multiple systems like Quore and GSS.​ 2\. Build an automated pipeline to fetch files from SharePoint and process them without manual intervention.​ 3\. Standardize and clean data coming from different Excel formats into a unified structured model.. 4\. Implement Medallion Architecture (Bronze, Silver, Gold) for scalable and organized data processing.​ 5\. Reduce reporting time and eliminate manual errors caused by Excel-based workflows. 6\. Create centralized, business-ready datasets to support analytics and decision-making.​ **Solution**​ 1\. Designed an automated data pipeline to fetch franchise reports from SharePoint whenever new files were uploaded.​ 2\. Implemented Power Automate Flow to trigger processing workflows and reduce manual intervention. 3\. Built Microsoft Fabric Pipelines to orchestrate data ingestion, transformation, and movement across different layers.​ 4\. Created business-ready aggregated datasets in the Gold layer optimized for analytics and reporting.​ 5\. Built interactive Power BI dashboards with filters, KPIs, and performance analytics for stakeholders.​ 6\. Enabled centralized reporting, replacing manual Excel-based workflows with automated insights.​ **Pre-Fabric Architecture Overview ​** ![]() **Before Fabric Implementation:​** 1\. Reports were generated from operational systems such as Quore and GSS and downloaded manually as Excel or PDF files.​ 2\. Files were manually uploaded and shared through SharePoint without structured automation or standardized pipelines.​ 3\. Data consolidation, cleaning, and transformation were performed manually in Excel, increasing dependency on human effort and introducing risks of errors.​ 4\. Reporting turnaround time was slow due to manual workflows and lack of automation.​ 5\. No centralized data architecture or structured processing flow to manage ingestion, transformation, and reporting.​ 6\. Limited analytics capabilities — reporting was primarily static rather than interactive or real-time.​ 7\. Difficult to maintain historical tracking, data versioning, and governance. 8\. Lack of a unified “single source of truth,” leading to inconsistent reporting across teams.​ **Post-Fabric Architecture Overview ​** ![]() **After Fabric Implementation:​** 1\. Implemented a Microsoft Fabric-based data platform with centralized storage, processing, and governance.​ 2\. Automated data ingestion pipelines fetch files directly from SharePoint, eliminating manual uploads.​ 3\. Power Automate flows detect new file uploads or incoming email attachments and automatically trigger processing workflows.​ 4\. Introduced Medallion Architecture (Bronze, Silver, Gold) to manage structured data lifecycle and improve data reliability.​ 5\. Bronze layer stores raw data.​ 6\. Silver layer applies PySpark transformations for data cleaning, normalization, schema standardization, and validation.​ 7\. Gold layer delivers curated, business-ready datasets optimized for reporting and analytics.​ 8\. Delta Tables enable incremental processing, reliable storage, and data versioning.​ 9\. Power BI dashboards provide interactive, real-time analytics and consolidated reporting.​ 10\. Established a centralized “single source of truth” for consistent decision-making across teams.​