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Intelligence · Automation · Advantage

The Library · Insights

Deep dives across data, automation & AI

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

Configuring Dataverse Calculated Columns and Multi-Table Rollup Columns in Model-Driven Apps
Power AppsPractitioner

Configuring Dataverse Calculated Columns and Multi-Table Rollup Columns in Model-Driven Apps

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.

24 min read
Handling Schema Evolution in Fabric Lakehouse Delta Tables: Adding Columns, Merging Incompatible Schemas, and Enforcing Constraints Across Medallion Layers
Microsoft FabricExpert

Handling Schema Evolution in Fabric Lakehouse Delta Tables: Adding Columns, Merging Incompatible Schemas, and Enforcing Constraints Across Medallion Layers

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.

29 min read
Building a Multi-Source Reconciliation Report in pandas: Comparing Actuals vs. Targets, Flagging Variances, and Exporting a Stakeholder-Ready Excel Summary
PythonExpert

Building a Multi-Source Reconciliation Report in pandas: Comparing Actuals vs. Targets, Flagging Variances, and Exporting a Stakeholder-Ready Excel Summary

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.

26 min read
Automating Windows Desktop Application Login and Session Management in Power Automate Desktop
Power AutomateFoundation

Automating Windows Desktop Application Login and Session Management in Power Automate Desktop

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.

18 min read
Configuring Dataverse Table Permissions in Model-Driven Apps: Mapping Security Roles to Tables, Privileges, and Access Levels for New Makers
Power AppsFoundation

Configuring Dataverse Table Permissions in Model-Driven Apps: Mapping Security Roles to Tables, Privileges, and Access Levels for New Makers

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.

19 min read
Branching Dataflow Gen2 Outputs to Multiple Destinations: Writing Transformed Data to a Lakehouse Table and a Warehouse Simultaneously
Microsoft FabricPractitioner

Branching Dataflow Gen2 Outputs to Multiple Destinations: Writing Transformed Data to a Lakehouse Table and a Warehouse Simultaneously

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.

22 min read
Building Summary Reports with pandas pivot_table and to_excel: Turning Aggregated Data into a Formatted, Multi-Sheet Workbook
PythonPractitioner

Building Summary Reports with pandas pivot_table and to_excel: Turning Aggregated Data into a Formatted, Multi-Sheet Workbook

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.

19 min read
Configuring Model-Driven App Dashboards: Building Interactive Charts, Lists, and System Dashboards for Dataverse Data
Power AppsFoundation

Configuring Model-Driven App Dashboards: Building Interactive Charts, Lists, and System Dashboards for Dataverse Data

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.

18 min read
Automating Windows Service and Process Management in Power Automate Desktop: Starting, Stopping, and Monitoring Applications Before and After Desktop Flow Execution
Power AutomateFoundation

Automating Windows Service and Process Management in Power Automate Desktop: Starting, Stopping, and Monitoring Applications Before and After Desktop Flow Execution

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.

18 min read
Creating and Managing Fabric Lakehouses with Notebooks: Reading External Files from OneLake, Writing Delta Tables, and Browsing Results in the Lakehouse Explorer
Microsoft FabricFoundation

Creating and Managing Fabric Lakehouses with Notebooks: Reading External Files from OneLake, Writing Delta Tables, and Browsing Results in the Lakehouse Explorer

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.

17 min read
Auditing and Reconciling Data Across Sources in pandas: Matching Totals, Flagging Discrepancies, and Building a Reconciliation Report
PythonExpert

Auditing and Reconciling Data Across Sources in pandas: Matching Totals, Flagging Discrepancies, and Building a Reconciliation Report

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.

26 min read
Calling the Fabric Lakehouse SQL Analytics Endpoint from Power BI Desktop: Connecting, Writing Measures, and Publishing a Report Without Direct Lake
Microsoft FabricFoundation

Calling the Fabric Lakehouse SQL Analytics Endpoint from Power BI Desktop: Connecting, Writing Measures, and Publishing a Report Without Direct Lake

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.

21 min read
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