Your hub for data & analytics learning
Explore Microsoft Fabric, Power BI, data engineering, AI, and the modern data stack. Choose a topic below: the dedicated Microsoft Fabric hub contains the Fabric curriculum, while this page brings all learning areas together.
Choose your learning area
Start with a platform or skill, then follow the guides relevant to your goal. Fabric has its own focused hub; the other collections below cover broader analytics and engineering topics.
Microsoft Fabric
A focused learning path for OneLake, Lakehouse, pipelines, notebooks, Warehouse, Real-Time Intelligence, and Fabric governance.
Data Engineering & Modern Stack
SQL transformation, table formats, data quality, orchestration, and preparation beyond one platform.
Compare Data Platforms
Architecture and tradeoffs across Fabric, Databricks, Snowflake, and other platforms.
Certification & Interview Prep
Choose Power BI or Fabric preparation resources that match your role.
Microsoft Fabric: a dedicated hub
Fabric is one learning area within Free Learning Resources. Use the child hub for its organized modules, role-based entry points, and Fabric-specific troubleshooting.
Open the Microsoft Fabric learning hub
Browse the full Fabric-only curriculum and choose a track.
Fabric Data Engineering
Follow ingestion, Dataflow Gen2, pipelines, notebooks, and mirroring guides.
Fabric Governance & Operations
Find OneLake security, governance, capacity, and operational guidance.
Power BI — In Depth
Power BI TMDL Tutorial — Edit Semantic Models as Code
Desktop and web TMDL view, version-control patterns, Git workflows, and team collaboration on semantic models. →
Model Context Protocol Power BI MCP Server
Connect AI agents to semantic models for automated DAX generation and bulk model operations. →
Agent Skills for Power BI — Complete Guide
Reusable AI agent capabilities purpose-built for Power BI workflows, and how to configure them for your team. →
Power BI Enhanced Report Format (PBIR) — Full Guide
What PBIR is, how it changes version control, and whether you should switch now or wait for your team. →
Power BI DAX with AI — From Prompt to Formula
Using Copilot and AI tools to write, explain, and optimize DAX — what works, what doesn’t, and what wastes time. →
AI in Power BI — Create Next-Level Reports in Seconds
The full breakdown of AI features in Power BI and which ones save meaningful time in production. →
Get Power BI AI-Ready — The Secret Behind Next-Level Insights
Semantic model hygiene, Q&A optimization, and the data prep steps that make AI features actually work. →
Direct Lake Falling Back to DirectQuery — Diagnosis & Fix
Why Direct Lake falls back, how to diagnose it in the Metrics App, and the exact steps to resolve it. →
DP-600 Direct Lake Performance Optimization
Performance optimization aligned to the DP-600 exam for Direct Lake semantic models. →
Power BI Calculation Groups — Full Guide
Calculation items, dynamic format strings, and avoiding measure explosion in large semantic models. →
DAX User-Defined Functions — Complete Guide
Reusable DAX logic with parameters, and how UDFs reduce repetition across large semantic models. →
Power BI Row-Level Security — Complete Guide
Static and dynamic RLS, role design, and how RLS interacts with Direct Lake and OneLake Security. →
Data Engineering & Modern Stack
Native dbt Jobs in Microsoft Fabric — Complete Guide
Run, schedule, and monitor dbt Core natively in Data Factory — no external orchestrator required. →
dbt Best Practices for SQL Transformation — Production Guide
Model organization, testing strategy, incremental patterns, and documentation standards for production dbt. →
Microsoft Web IQ — Complete Guide
Real-time grounding from the open web for agentic workflows, and how it complements Fabric IQ and Work IQ. →
Microsoft Work IQ API — Complete Guide
Organizational context grounding for agents — Microsoft Graph signals, permissions model, and developer setup. →
Microsoft Fabric RAG Tutorial — Build Trustworthy AI
Retrieval-Augmented Generation on Fabric: architecture, indexing, and grounding your AI outputs. →
Data Observability vs Data Quality — A Practical Guide
What each discipline covers, where they overlap, and how to build both into a modern data platform. →
Skrub Library — Smarter Data Preparation for ML
What Skrub is, how it handles dirty tabular data, and where it fits in a modern data engineering workflow. →
Prompt Engineering Tutorial for Data Engineers
Chain-of-thought, few-shot prompting, and structured output techniques that matter for data work. →
Agentic Data Engineering — Build AI-Driven Pipelines
Multi-agent orchestration, automated data engineering workflows, and Fabric AI Agent integration patterns. →
Airflow KubernetesPodOperator Troubleshooting
Find the existing general Airflow troubleshooting guide.
AI & Agents for Data Professionals
Explore general AI skills and tools here. Fabric-specific Data Agents and AI lessons also live in the Fabric hub.
Certification & Interview Preparation
Choose a product and role before selecting preparation material. These are independent learning guides, not Microsoft-issued courses or exam guarantees.
Fabric Certification & Interviews
Find DP-600, DP-700, and Fabric interview resources in the dedicated hub.
Build Power BI Skills
Explore semantic modeling, DAX, reporting, and practical Power BI learning guides.
Platform Comparisons — Make the Right Call
Microsoft Fabric vs Databricks — Full Comparison
Architecture, workloads, pricing, performance, and which platform fits which team. No vendor bias. →
Microsoft Fabric vs Snowflake — Architecture & Cost Analysis
Data warehouse capabilities, compute model differences, and real migration cost considerations. →
Microsoft Fabric vs Google BigQuery — Head-to-Head
Query engines, storage models, real-time capabilities, and multi-cloud considerations compared. →
Microsoft Fabric vs Azure Synapse — Full Comparison & Migration Guide
What carries over, what doesn’t, the Pipeline Migration Assistant, and what the migration actually costs. →
Apache Iceberg vs Delta Lake — Format Comparison
Table format internals, ecosystem support, time travel, schema evolution, and Fabric compatibility. →
Unity Catalog vs OneLake Security — Governance Compared
How Databricks’ Unity Catalog and Fabric’s OneLake security model approach access control differently. →
Microsoft Fabric vs Power BI — What’s the Difference?
Clears up the most common confusion in the ecosystem: Power BI is a workload inside Fabric, not a competing product. →
Common Errors — Fixed Fast
OneLake Shortcut Authorization Failed — Cross-Workspace Fix
Dataflow Gen2Dataflow Gen2 Error 20302 — Cause & Resolution
CopilotPower BI Copilot “Something Went Wrong” — Fix
Copy ActivityCopy Activity CSV Column Not Found — BOM Character Fix
PySpark · DeltaPy4JJavaError When Saving Delta Table — Fix
AirflowAirflow KubernetesPodOperator 403 Forbidden — Fix
Apache SparkSpark Shuffle Partitions Optimization Tutorial & Fix
SecurityCloud Security Tips for Data Platforms
Power BIPower BI Gateway Error — Fix
Power BIPower BI OLE DB or ODBC Error — Fix
Power BIPower BI SqlDumper.exe CMD Window — Fix
Selected Guides & Deep Dives
Native dbt Jobs in Microsoft Fabric — Complete Guide
Run dbt Core natively inside Data Factory. Setup, scheduling, CI/CD patterns, and how it compares to dbt Cloud orchestration. →
Power BI TMDL Tutorial — Edit Semantic Models as Code
Tabular Model Definition Language in Desktop and the new web editor. Version control, Git integration, and team workflows. →
Model Context Protocol — Power BI MCP Server Guide
Connect AI agents to Power BI semantic models. Automated DAX generation, bulk model operations, and setup walkthrough. →
Fabric Data Agent Code Interpreter — Dynamic AI Analytics
Python-driven visualizations and deep analytics from the Data Agent, surfaced directly inside Microsoft Teams. →
Microsoft Fabric Apps — Complete Developer Guide
Deploy governed application backends directly on Fabric. SQL DB, Auth, and Static Hosting via the Rayfin SDK. →
Microsoft Fabric IQ — Domain-Aware AI Layer Explained
How Fabric IQ grounds agents in business context rather than raw tables, and where it fits alongside Copilot and Data Agents. →
Pricing figures, product availability, and platform details referenced across this site are based on official documentation at the time of writing and are updated regularly. Always verify current information at official vendor documentation before technology or purchasing decisions. UIG Data Lab is an independent publication — not affiliated with, endorsed by, or sponsored by Microsoft Corporation, Databricks, Snowflake, or any other vendor mentioned.
About this learning hub
What topics does Free Learning Resources cover?
This is the parent hub for Microsoft Fabric, Power BI, data engineering, AI, and the modern data stack. Start with a topic card to find the relevant collection.
Where is the Microsoft Fabric curriculum?
Open the dedicated Microsoft Fabric hub for its platform-specific modules, tracks, and troubleshooting resources.
Where should I learn general Power BI or data engineering?
Use the Power BI and Data Engineering sections on this page. General DAX, TMDL, SQL transformation, data quality, and orchestration topics are kept here rather than mixed into the Fabric-only curriculum.
Does reading a guide mean its cloud exercise is free?
No. Reading and cloud execution have different requirements. Hands-on exercises can require licenses, capacity, permissions, or paid services. Check each guide and the vendor’s current pricing before running resources.
Review scope: the hub structure was updated on 23 October 2026. Linked articles retain their own review history; this is not a claim that all technical content was re-verified today. These resources are independent and do not guarantee certification readiness.