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Business intelligence, thoughtful automation, and the engineering behind it. Explore practical guides and interactive projects built to make your next decision clearer.
Choose what you want to build. Find a practical starting point, then go deeper at your own pace.
04 pathways One place to beginConnect the dots between OneLake, Direct Lake, and your Fabric certification roadmap.
Turn complex data into clear decisions with thoughtful dashboards and stronger analytical models.
Explore rendering, technical SEO, and the performance decisions behind fast web experiences.
Discover practical orchestration patterns for connecting tools, agents, and repeatable workflows.
Practical guides on data, intelligent workflows, and the systems behind them.
Master SQL Window Functions with this enterprise 2026 guide. Complete architectural deep dive into ROW_NUMBER(), RANK(), DENSE_RANK(), the OVER() clause, PARTITION BY, window frames, 10-stage execution order, and query performance tuning in SQL Server & Microsoft Fabric.
Master Power BI Calculation Groups in 2026. A comprehensive enterprise architecture guide covering calculation items, precedence resolution, dynamic format strings, Tabular Editor 3 C# automation, and semantic model optimization.
A deep dive into Microsoft Fabric Data Factory and Azure Data Factory, examining feature parity, cost models, and a pragmatic migration strategy for enterprise data architects and engineers looking towards 2026.
Dive deep into Microsoft Fabric's Direct Lake mode, exploring its architecture, strategies for eliminating DirectQuery fallback, and advanced enterprise performance tuning techniques for optimal, real-time analytics by 2026.
Master enterprise-grade CI/CD for Microsoft Fabric. This guide covers Git integration, automated testing, deployment pipelines, and API-driven automation for robust data platform development.
Build Microsoft Fabric Real-Time Intelligence with Eventstream, Eventhouse, KQL and Activator. Includes queries, alert design, costs and a production checklist.
Follow your curiosity through the tools, systems, and ideas that shape better engineering.
View the full libraryOneLake / Lakehouse / Real-time
DAX / Modeling / Visual storytelling
Queries / Architecture / Performance
Pipelines / Analytics / Data tooling
Rendering / Web architecture / Speed
Discovery / Indexing / Search intent
Connect your stack. Build smarter workflows.
Explore a subject from the inside out.
Three focused collections for your next deep dive.
Understand how OneLake, Direct Lake, and pipelines fit together.
Build sharper models and dashboards that make complex data useful.
Connect rendering, discoverability, and performance in Next.js.
Practical ideas deserve practical next steps. Explore the reasoning, try the implementation, and adapt it to your own work.
Architecture, context, and tradeoffs.
Patterns, examples, and implementation.
Measure results in your own environment.
A few useful places to return to when you need a clearer answer.
Architecture & certification
Analytics engineering
SQL patterns & query design
Sharper analytical models
Rendering & discoverability
Go beyond the overview.
See how the pieces fit together.
Work through targets, returns, and source reconciliation in a small sales model.
Separate valid JSON, schema conformance, and factual accuracy in an extraction workflow.
Explore storage choices and validate query performance against your own workload.
Design a source-tracked draft queue with explicit editorial review before publication.
A starting point for the questions behind your data, your tools, and your next skill.
Find a guide in the directoryMicrosoft Fabric is an all-in-one analytics solution for enterprises that covers everything from data movement to data science, Real-Time Analytics, and business intelligence. It integrates separate services like Azure Synapse, Data Factory, and Power BI into a single, unified SaaS platform built on an open OneLake data foundation.
Choose by role: DP-600 covers Fabric analytics engineering, DP-700 covers Fabric data engineering, and DP-800 covers AI-enabled database development across Microsoft SQL platforms. Compare the current Microsoft Learn study guides with the work you want to do.
Direct Lake is a ground-breaking semantic model capability for analyzing very large volumes of data in Power BI. It allows loading data directly from Delta tables in OneLake into the Power BI engine without converting it or executing queries in DirectQuery or Import modes, keeping dashboard rendering speeds incredibly fast.
Begin by mastering clean star-schema data modeling practices, followed by learning fundamental DAX calculations. We recommend official Microsoft Learn pathways, running hands-on exercises with real datasets, and studying technical blogs like our collection to understand enterprise patterns.
For cloud data engineers, Snowflake SnowPro Core or Microsoft Azure Database Administrator certifications are highly valued. However, a deep understanding of standard ANSI SQL, query plan analysis, and indexing mechanics is far more critical in day-to-day work than any specific certificate.
Our typical technical stack includes Microsoft Fabric, Power BI, PostgreSQL, DuckDB, Python (for ETL pipelines), dbt (for data transformations), and n8n (for cloud service and API workflow orchestrations).