Metadata Driven Framework
Git Hub Code Repo : https://github.com/NandanHegde15/MSFTFabric-Projects/blob/main/Metadata%20Driven%20Framework/README.md Demo : https://www.youtube.com/watch?v=Z7mjHmX8-40 Metadata Driven Framework is a Microsoft Fabric-based end-to-end healthcare analytics platform . This project demonstrates modern data engineering practices including: Multi-layer data architecture (Raw → Silver → Gold layers) FHIR healthcare data modeling with support for patients, claims, coverage, and organizations Automated data pipelines for ingestion, transformation, and aggregation Power BI semantic models for enterprise analytics and reporting Row-level security for data governance and privacy AI-powered insights using Copilot & Data Agent capabilities Authors : Hemanth Kotha, Nandan Hegde https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DZ7mjHmX8-40Medallion Architecture in Microsoft Fabric: Building an AI-Ready Data Pipeline
Video Walkthrough Link------------> (https://raw.githubusercontent.com/trivedisunita/Fabric-Data-Factory-Contest/main/Fabric%20Short%20Video2.mp4) This project presents an end-to-end data pipeline built for the Data Factory Challenge using Microsoft Fabric. The objective was to transform raw job salary data into a structured, analytics-ready format for insights. ------------- Architecture Overview-------- Step1- ##Bronze Layer:-- Raw data is ingested into a Lakehouse from a SharePoint source without transformations, ensuring data is preserved in its original format. Step 2-- ##Silver Layer:-- Data is processed using Data Factory pipelines and stored in a Data Warehouse schema. Transformations include data cleaning, handling null values, and standardizing fields. SQL scripts and Copilot were used to assist in transformations. Step--3 ##Metadata Pipeline:--- Metadata-driven pipeline is implemented to manage and monitor data flow across layers. It enables dynamic execution, parameter handling, and improves pipeline scalability and maintainability within Microsoft Fabric. Step--4 ##Gold Layer:-- Data is modeled using dbt to create fact and dimension tables. A star schema is built for efficient querying, with reusable transformations such as converting coded fields into readable formats. Step--5 ##Semantic Model & Reporting:-- An AI-ready semantic model is created and used in Power BI. The model is optimized by selecting relevant columns and defining structure for better performance and accurate insights. Interactive reports are built on top of this model, enabling natural language queries using Copilot and delivering reliable business insights. https%3A%2F%2Fyoutu.be%2FskgWJyBPMcsDiscord Ontology
This ontology models the Fabric Community Discord Server and how it operates. It captures the key concepts of members, access control, communication, and moderation that govern the day to day server life. Users join and become members, earn roles, access channels, post messages, and if they're naughty, get dealt with through moderation actions. Rather than modelling Discord's underlying infrastructure, the focus is on the operational system running on top of it: who belongs, what they're allowed to do, how they communicate, and how the community keeps itself in check. The relationships tell a story about how access, identity, and behaviour interlock. A member earns a role, typically through a bot, and that role grants access to specific channels. Inside those channels, members post messages. Messages can then be turned into threads for deeper conversation, or they can collect reactions. Bots monitor messages and can respond if required. When someone steps out of line, a moderation action gets issued, typically automatically by a bot. Roles can get revoked, and access gets restricted, or members can be removed from the community entirely. It's a feedback loop between participation and permission, and it's the kind of structured reasoning an AI agent could actually use to answer questions like "What can this member see?", "Who moderated this user and why?", or "Which channels are open without a verified role?" The Ontology can be found here: https://github.com/taylorsamy/Ontology-Playground/blob/main/catalogue/community/tayloramy/discord_ontology/discord-server-ontology.rdf https://microsoft.github.io/Ontology-Playground/#/share/
