The Library · Insights
Deep dives across data, automation & AI
978 in-depth articles — from Excel foundations to production machine learning. Filter by topic or difficulty to find exactly what you need.
PythonExpert
Building a pandas Data Quality Scorecard: Automating Completeness, Consistency, and Validity Checks Across Every Column Before Analysis
Bad data doesn't announce itself — it hides in nulls, inconsistent categories, out-of-range values, and pseudo-null strings until it breaks your analysis. This lesson walks you through building a complete, reusable data quality scorecard in pandas that interrogates every column before a single analysis runs, scores failures by severity, and exports a stakeholder-ready Excel report.
24 min read
Power AppsPractitioner
Configuring Dataverse Auto-Numbering Columns and Sequence Patterns in Model-Driven Apps
Learn how to design and configure Dataverse auto-numbering columns that generate reliable, auditable record identifiers for procurement, compliance, and business process workflows. Covers format string patterns, seed management, API configuration, and production deployment strategies.
22 min read
Power AutomateExpert
Automating Database Queries and Record Updates from Power Automate Desktop: Connecting to SQL Server, Executing Queries, and Writing Results to Windows Applications
Learn how to connect Power Automate Desktop directly to SQL Server, execute parameterized queries safely, iterate over results, and write data into Windows applications — with production-grade error handling and multi-bot concurrency patterns built in.
29 min read
Microsoft FabricPractitioner
Orchestrating Multi-Notebook Workflows in Microsoft Fabric: Using Pipeline Notebook Activities, Activity Dependencies, and Output Variables to Chain PySpark Transformations Across Medallion Layers
Learn how to wire Fabric PySpark notebooks into a production pipeline using Notebook activities, On Success/On Failure dependencies, and mssparkutils.notebook.exit() output variables. Build a complete Bronze→Silver→Gold medallion pipeline that passes context between stages and handles failures gracefully.
20 min read
Power AppsPractitioner
Configuring Dataverse Table Queues and Routing Rules in Model-Driven Apps: Managing Work Assignment, Queue Item Lifecycles, and Team-Based Record Distribution
Learn how to configure Dataverse queues and routing rules to build a structured work assignment system in model-driven apps. This lesson covers queue item lifecycles, team-based distribution patterns, and automatic case routing from scratch.
24 min read
PythonFoundation
Sampling, Sorting, and Inspecting DataFrames in pandas: head, tail, sample, sort_values, and nlargest for Quick Data Exploration
Before you analyze anything, you need to orient yourself in your data. This lesson teaches you the five pandas methods every analyst uses in the first two minutes with a new dataset — and how to combine them into a fast, reliable exploration workflow.
15 min read
PythonExpert
Forecasting Seasonal Trends in pandas: Decomposing Time Series into Trend, Seasonality, and Residuals for Business Reporting
Learn how to decompose business time series into trend, seasonal, and residual components using pandas and statsmodels. Go from raw monthly data to formatted seasonal forecasts and stakeholder-ready Excel reports.
25 min read
Microsoft FabricPractitioner
Building a Star Schema in a Fabric Lakehouse Gold Layer: Creating Dimension and Fact Delta Tables with PySpark for Direct Lake Reporting
Learn how to design and build a production-quality star schema in your Fabric Lakehouse Gold layer using PySpark — covering surrogate key strategy, dimension and fact table construction, orphan validation, and post-write optimization for Direct Lake reporting in Power BI.
22 min read
Power AppsPractitioner
Configuring Dataverse Search: Enabling Relevance Search, Configuring Searchable Tables and Columns, and Tuning Quick Find for Model-Driven Apps
Most Dataverse Search problems aren't data problems — they're configuration problems. This lesson teaches you exactly how to enable Dataverse Search, control which tables and columns are indexed, and tune Quick Find views so users actually find what they're looking for.
24 min read
Power AppsFoundation
Configuring Model-Driven App Quick Forms and Card Forms: Displaying Related Record Summaries in Lookups and Subgrids
Learn how to build Quick Forms and Card Forms in Power Apps model-driven apps so users see rich, contextual summaries of related records directly inside lookup flyouts and subgrids — no navigation required. This hands-on lesson covers creating, configuring, and troubleshooting both form types from scratch.
17 min read
PythonPractitioner
Combining String, Date, and Numeric Transformations in a pandas Data Cleaning Pipeline: Standardizing Real-World Columns Before Analysis
Real exports are never clean — dates in four formats, currency fields as strings, category columns with a dozen spellings of the same value. This lesson builds a complete, production-grade cleaning pipeline that handles all three mess types together, with validation built in.
18 min read
PythonPractitioner
Cohort Analysis in pandas: Calculating Retention, Churn, and Lifetime Value from Transaction Data
Learn how to turn a raw transaction log into a complete cohort analysis in pandas — including a retention matrix, period-over-period churn rates, and cumulative customer lifetime value broken down by acquisition cohort. Covers everything from cohort assignment to a reusable production function.
20 min read