Fabric Lakehouse Health Checks Make Optimization Practical. Here’s the Runbook.
A practical runbook for using sp_get_table_health_metrics to diagnose Lakehouse table health before spending Spark compute on maintenance.
Data Ninja AI Lab
Building practical data systems with Microsoft Fabric, Power BI, and AI.
I use this lab to publish practical articles, demos, and code around Microsoft Fabric, Power BI, analytics engineering, automation, and AI systems.
My goal is simple: turn real implementation work into clear patterns other data professionals can use. Less theory, more decisions, tradeoffs, architecture, and working examples from the messy middle of building reliable data platforms.
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Latest articles
Fabric Warehouse Brings AI Enrichment Into T-SQL. Here’s the Practical Guide.
A practical guide to the preview AI functions in Fabric Data Warehouse: classify, extract, summarize, translate, fix grammar, generate responses, and materialize outputs safely.
Fabric Data Factory Makes Multi-Cloud Integration Practical. Here’s the Architecture Checklist.
A practical architecture checklist for using Fabric Data Factory to build multi-cloud data flows with clear landing zones, identity paths, transform boundaries, cost rules, failure contracts, and trusted outputs.
Fabric Warehouse Can Clean Messy Text Now. Here’s the Data Quality Playbook.
A practical guide to the new Fabric Data Warehouse string-processing preview: how to profile, normalize, validate, match, review, and audit messy text inside the warehouse.
Fabric Real-Time Dashboards Just Became Much More Useful for Live Operations
A practical guide to the new Real-Time Dashboard updates: AI-assisted visual authoring, Time Series visualization, Live Refresh, and the operational checklist that makes them useful.
AI Can Build Power BI Reports Now. Here’s the Playbook I’d Use First.
A practical guide to Microsoft’s Power BI agent skills, top use cases, install path, PBIR workflow, screenshot loop, and first pilot playbook.
Fabric IQ Is GA. This Is the Context Layer I’ve Been Waiting For.
Why Fabric IQ becoming generally available matters for AI agents, semantic models, graph reasoning, ontology, and governed business context.
Build Power BI Columns That Adapt to Each User
A practical guide to user-aware calculated columns, Expression Context, localization, virtual columns, and security-aware model patterns.
Copy Job CDC with SQL estate is now GA in Microsoft Fabric
What the GA release means for SQL estate replication, SCD Type 2 history, soft deletes, and production Fabric architecture.
Fabric AI Functions Put GenAI Where the Data Work Already Happens
What changed with Fabric AI Functions, why multimodal support matters, and how teams can use AI enrichment inside real pandas and Spark workflows.
Put Copilot Metadata Where Your Team Can Review It
Why Prep data for AI, verified answers, and Copilot metadata should be treated like semantic model engineering artifacts.
The Power BI Setting That Makes Semantic Models Safer
Why Outbound Access Protection for semantic models turns workspace network rules into a real Power BI governance decision.
Before You Put a Fabric AI Agent in Production, Steal This Checklist
A practical production checklist for Fabric AI Agents, focused on access paths, ownership, auditability, and safe use with real business data.
Your Microsoft Fabric Bill Has a OneLake Problem
How OneLake storage tiers push Fabric teams toward better ownership, lifecycle rules, and practical FinOps habits.
Repository Intelligence: The Real Shift Behind Microsoft Fabric + Git
Why Git-backed Fabric assets can become a context layer for AI-assisted analytics engineering.