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Supercharge Microsoft Fabric — a hands-on Fabric reference for regulated industries: casino & gaming, Tribal Nations, and federal agency analytics, on F64 capacity

Supercharge Microsoft Fabric

A hands-on Microsoft Fabric reference for data teams in regulated industries — it starts in casino & gaming, bridges through Tribal Nations gaming and health, and extends out to federal agency analytics. Same medallion + governance backbone, applied across each domain.

Real-time insights · Medallion Architecture · Regulatory Compliance · Direct Lake BI

Personal project — not an official Microsoft product

This is a personal, community-built reference maintained by Frank Garofalo. It is not a sanctioned Microsoft deliverable, nor official Microsoft Fabric product documentation, and opinions here are the author's own. The compliance pages (FedRAMP, HIPAA, NIST 800-53, NIGC MICS, Title 31/BSA, etc.) are reference control mappings for education and POC scoping — not authorizations, attestations, or certifications.

Quick Start Tutorials


Three Core Paradigms

This reference is built on three paradigms that define how data flows from source to insight inside Microsoft Fabric.

OneLake is the unified storage layer. It's Delta Lake–native — Fabric engines read and write Delta tables to a single lake with no data movement — and interoperates with Apache Iceberg via metadata virtualization (shortcuts and the Iceberg/Delta translation layer), so Iceberg readers and writers can work against the same data.

Medallion Architecture (Bronze → Silver → Gold) organizes that data by quality tier. Bronze captures raw ingestion, Silver cleanses and validates, Gold produces business-ready KPIs and star schemas.

Direct Lake connects Power BI semantic models straight to Gold-layer Delta tables in OneLake — low-latency analytics with no import step and no scheduled refresh. (On large or over-limit models it can fall back to DirectQuery, and cold caches warm on first access.)

Together they give you a single pipeline from raw events to executive dashboards, with governance enforced by Microsoft Purview at every layer.


How this relates to CSA-in-a-Box

This project is a Microsoft Fabric reference — use it once you've committed to Fabric (the SaaS, Microsoft-managed platform) and want hands-on patterns, tutorials, POC agendas, and governance mappings on F64 capacity.

Its sibling, CSA-in-a-Box, is the Azure-native, build-your-own PaaS/IaaS alternative: the same Data Mesh + Data Fabric + Data Lakehouse capabilities assembled from Azure services you own and operate — for teams who can't get Fabric yet, or who deliberately don't want SaaS and need full control of the environment. CSA Loom is the productized, Fabric-like console layer over CSA-in-a-Box.

Which one do I use?

Your situation Use
Fabric is GA in your cloud and you want it (SaaS, Microsoft-managed) Microsoft Fabric — and this repo for hands-on depth
Fabric isn't available in your cloud yet (Azure Government / DoD / IC) CSA-in-a-Box
You could get Fabric but won't take SaaS — you need control / sovereignty / custom networking CSA-in-a-Box (a permanent choice, by design)
You want the CSA stack with a Fabric-like console + guided deploy CSA Loom

Start Here

  • Quick Start


    Prerequisites, Azure setup, one-click Bicep deployment

    Get started

  • Tutorials


    50+ self-paced, hands-on tutorials from Bronze ingestion to AI/ML

    Browse tutorials

  • Architecture


    System design, component overview, data flow diagrams

    View architecture

  • 3-Day POC Agenda


    A curated subset of the tutorials, packaged as a guided workshop: Foundation → Transformation → BI & Governance

    View agenda


Choose Your Path

  • Data Engineers


    PySpark notebooks, pipelines, ETL, medallion implementation

    Bronze layer tutorial

  • BI Developers


    Direct Lake, Power BI semantic models, DAX measures

    Direct Lake tutorial

  • Security & Compliance


    Microsoft Purview governance, gaming internal controls (NIGC MICS), and anti-money-laundering reporting (CTR/SAR)

    Governance tutorial

  • Real-Time Analytics


    Eventstreams, Eventhouse, KQL for streaming workloads

    Real-time tutorial


Feature Documentation

  • Fabric IQ


    Natural language data exploration with Ontology & Plan layers

    Fabric IQ

  • Real-Time Intelligence


    Eventstreams, Eventhouse, KQL, Business Events, Maps

    RTI

  • AI Copilot


    Copilot Studio integration and governance configuration

    Copilot

  • Data Mesh


    Enterprise data mesh patterns with Fabric domains

    Data Mesh

View all features


Compliance & Governance

This reference covers casino/gaming regulations (NIGC MICS, Title 31/BSA, IRS Gaming) and supports 8 federal agency domains — USDA, SBA, NOAA, EPA, DOI, DOT/FAA, Tribal Healthcare, and DOJ.

These are reference mappings, not authorizations

The compliance and governance pages illustrate how Fabric controls can map to each framework, for education and POC scoping. They are not ATOs, attestations, audits, or certifications, and they don't represent the compliance posture of any production system.

Framework Coverage
NIGC MICS Minimum Internal Control Standards
Title 31/BSA Anti-money laundering, CTR/SAR
IRS Gaming W-2G, 1042-S reporting
State Gaming Commissions Jurisdiction-specific requirements

Security documentation


  • GitHub Repository


    Source code, issues, and releases

    Open on GitHub

  • Documentation


    Full documentation index and guides

    Browse docs

  • Infrastructure


    Bicep IaC modules for Azure deployment

    View infra

  • Cost Estimation


    F64 capacity sizing, commercial vs Azure Government. Pricing changes often — verify current rates on the Azure pricing calculator.

    Cost details


Currency: Last reviewed 2026-05-29. Microsoft Fabric features and pricing change frequently — verify against Microsoft Learn and the Azure pricing calculator before relying on any figure here.

License: MIT · Maintained by: Frank Garofalo · A personal/community project — not affiliated with, sponsored by, or endorsed by Microsoft.

View on GitHub