1261 in-depth articles — from Excel foundations to production machine learning. Filter by topic or difficulty to find exactly what you need.

Learn how to configure Dataverse calculated columns and rollup columns to aggregate related record data for forms, views, and business logic. Build an Account Health scoring system using real rollup and formula patterns with no code.

Schema changes in production Delta lakehouses cascade across medallion layers in ways that break pipelines, corrupt reports, and silently produce wrong results. This deep-dive lesson teaches you exactly how Delta Lake enforces and evolves schemas, how to build drift detection into your pipelines, and how to use CHECK and NOT NULL constraints to enforce data quality where it matters.

Learn how to build a production-quality reconciliation pipeline in pandas that merges actuals, targets, and adjustments from multiple sources, applies tiered variance flag logic, and exports a formatted multi-sheet Excel workbook — complete with conditional formatting, frozen panes, and an executive scorecard. This is the report your CFO actually wants.

Learn how to launch Windows applications programmatically, handle authentication prompts reliably, and keep sessions active throughout your automation. This lesson takes you from basic app launching through production-grade credential handling and session recovery — the skills every RPA developer needs before anything else.

Misconfigured table permissions are the most common way model-driven apps go wrong after launch. This lesson teaches new makers how Dataverse security roles, privilege types, and access levels work together — with real-world examples, step-by-step role configuration, and a hands-on exercise to test your understanding.

Dataflow Gen2 lets you attach multiple output destinations to a single query — run your transformation once and write results to both a Fabric Lakehouse table and a Warehouse table simultaneously. This lesson teaches you the complete pattern: from Power Query transformation to dual-destination configuration, data type gotchas, and production-ready pipeline orchestration.

Learn how to turn raw transaction data into a professional, multi-sheet Excel workbook using pandas pivot_table and openpyxl. This lesson covers building multiple pivot summaries, applying header styles and number formats, adding a cover sheet, and structuring the whole pipeline as a reusable script.

Model-driven app dashboards give your users live, interactive summaries of Dataverse data without spreadsheets or manual reports. This lesson teaches you how to build charts, assemble system dashboards, and set them as the default app experience — step by step with a real scenario.

Most RPA failures happen before the bot touches a single button — the environment simply was not ready. Learn how to check, start, stop, and monitor Windows services and processes in Power Automate Desktop so your flows manage their own runtime environment reliably, day or night.

Learn how to use Spark notebooks in Microsoft Fabric to read CSV and Parquet files from OneLake, write clean Delta tables to the lakehouse Tables zone, and validate your results in the Lakehouse Explorer — the complete data engineering loop from raw files to queryable data. This foundation-level lesson explains every step from first principles with realistic examples and working PySpark code.

When your ERP, CRM, and finance spreadsheet all show different numbers, you need a systematic way to find out who's wrong and by how much. This expert-level lesson teaches you to build a complete data reconciliation pipeline in pandas — from normalizing heterogeneous sources, through row-level mismatch detection, to a formatted multi-sheet Excel report stakeholders can actually use.

Learn how to connect Power BI Desktop to a Fabric lakehouse SQL Analytics Endpoint, build a star schema with DAX measures, and publish a production-ready report — no Direct Lake required. This lesson explains every step from finding the connection string to scheduling refreshes, with clear guidance on when to use this approach over Direct Lake mode.