This repository contains demos and guides for building a well-architected framework for a Microsoft Fabric enterprise-level data platform. These demos are intended as a guide. For official guidance, support, or more detailed information, please refer to Microsoft's official documentation or contact Microsoft directly.

/Step by step reference implementation for setting up data agents and integrating agent with Copilot Studio

Fabric Basic Workshop, these guides will elaborate on the standard architecture or features commonly used across industries.

Designed to highlight the power of Microsoft Fabric in the retail sector. How Fabric can serve not only as a unified data platform but also as a strategic foundation for preparing data for future AI-driven use cases

Quick overview of what IOPS means in a MySQL server and explore a few example scripts to configure it

Quick overview of what is Azure Synapse and demo of how to Dynamically Remove Blank Spaces to create a view

This repository contains demos and guides for Optimizing Azure Database Performance by Freeing Up Unused Space. These demos are intended as a guide. For official guidance, support, or more detailed information, please refer to Microsoft's official documentation or contact Microsoft support directly.

Automate and standardize reusable date hierarchies in Power BI and Microsoft Fabric models using templates, scripts, and best practices.

Comparison of approaches for handling cookie and CSRF token management. For official guidance, support, or more detailed information, please refer to Microsoft's official documentation or contact Microsoft directly.

This tool is intended for estimation purposes only. A more comprehensive Microsoft tool is now public preview General Availability (GA). Please stay tuned for updates. For official guidance, support, or more detailed information, please refer to Microsoft's official documentation or contact Microsoft directly.

Practical examples and guidance for working with Azure database services (setup, performance tuning, data modeling, and best practices, etc)