The Library · Insights
Deep dives across data, automation & AI
979 in-depth articles — from Excel foundations to production machine learning. Filter by topic or difficulty to find exactly what you need.
PythonFoundation
Conditional Columns and Bucketing in pandas: Creating New Fields with np.where, cut, and map
Learn how to create new columns in pandas using np.where for conditional flags, pd.cut for numeric bucketing, and .map() for code-to-label substitution. Three essential tools that replace slow loops and Excel workarounds with fast, readable Python.
15 min read
Power AppsPractitioner
Configuring Dataverse Polymorphic Lookups and Customer Columns: Modeling Multi-Table Relationships in Model-Driven Apps
Standard lookups point to one table. But real business data is messier than that — a customer might be an Account or a Contact, an expense might belong to a Project or a Department. Learn how Dataverse polymorphic lookups, Customer columns, and Regarding columns solve this cleanly, and how to configure them end-to-end in model-driven apps.
24 min read
PythonFoundation
Reshaping Wide and Long Data for Reporting: When and How to Use melt, pivot, and unstack in pandas
Wide data is easy to read but hard to analyze. Long data is easy to analyze but hard to present. This lesson teaches you exactly when to use melt, pivot, and unstack in pandas — with realistic examples and a clear workflow for converting between formats.
14 min read
Power AutomatePractitioner
Automating Internet Explorer and Citrix-Hosted Applications in Power Automate Desktop: Selector Strategies, Session Management, and Reliable Data Extraction from Virtual Environments
Legacy systems don't give up their data easily — especially when they're running inside Citrix or IE. This lesson teaches you how to build Power Automate Desktop flows that reliably extract data from virtual environments using layered selector strategies, OCR, image recognition, and production-grade session management.
25 min read
Power AppsPractitioner
Configuring Dataverse Virtual Tables: Connecting External Data Sources to Model-Driven Apps Without Migration
Virtual tables let you surface live data from SQL Server, REST APIs, and OData services directly inside your model-driven app — no ETL, no data copy, no sync. This lesson teaches you to configure OData data sources, map columns, build cross-system relationships, and handle the security and performance challenges that come with production virtual table deployments.
26 min read
Microsoft FabricPractitioner
Parameterizing Dataflow Gen2 Queries with Pipeline Integration: Passing Dynamic Values to Power Query for Reusable Ingestion Flows
Learn how to define Power Query parameters in Dataflow Gen2 and pass runtime values from Fabric pipelines — building a single, reusable ingestion flow that adapts to different regions, time periods, or environments without duplicating logic. Includes a full hands-on exercise and troubleshooting guide.
21 min read
PythonExpert
Detecting and Resolving Data Quality Issues Across Merged DataFrames: Diagnosing Join Mismatches, Duplicate Keys, and Row Count Surprises in pandas
Silent join bugs — row multiplication, unmatched keys, type mismatches — are the most dangerous errors in data analysis because pandas won't warn you. This lesson gives you a complete diagnostic toolkit: pre-merge key profiling, cardinality analysis, post-merge row count auditing, and defensive merge wrappers that catch problems before they corrupt your analysis.
28 min read
Power AutomateFoundation
Reading and Writing to CSV and Text Files in Power Automate Desktop: Parsing Delimiters, Handling Headers, and Looping Through Records
Learn how to read CSV and text files in Power Automate Desktop, parse delimited records, handle header rows correctly, and write processed data back to files. A hands-on guide for automating flat-file workflows from first principles.
16 min read
Microsoft FabricFoundation
Loading Data into a Fabric Warehouse with COPY INTO and the Pipeline Copy Activity: Bulk Ingestion from Parquet and CSV Files in OneLake
Learn how to bulk-load Parquet and CSV files from OneLake into a Microsoft Fabric Warehouse using COPY INTO and the Pipeline Copy Activity. This hands-on lesson covers file path patterns, CSV configuration options, column mapping, and post-load verification — everything you need to run production-grade ingestion jobs.
19 min read
Power AppsFoundation
Configuring Model-Driven App Column Properties: Data Types, Required Fields, and Display Settings for Dataverse Tables
Column properties are the difference between a model-driven app that produces clean, consistent data and one that's constantly fighting user errors and dirty records. This lesson teaches you how to choose the right data type, configure required fields at the right layer, and set up display settings that guide users toward correct data entry — without writing code.
21 min read
Power AutomateExpert
Automating Image-Based UI Interactions in Power Automate Desktop: Using Screen Scraping, Image Recognition, and Coordinate-Based Actions When Selectors Fail
When Power Automate Desktop selectors can't reach an application — Citrix streams, custom-rendered controls, broken accessibility trees — image recognition and coordinate-based automation take over. This expert-level lesson teaches you how to build reliable, production-grade automations using template matching, OCR, and dynamic coordinate calculation, including fallback chains that gracefully degrade between all three techniques.
34 min read
PythonPractitioner
Weighted Averages, Percent of Total, and Custom Aggregations in pandas: Going Beyond sum and mean in groupby
Learn to compute revenue-weighted averages, percent-of-total share metrics, and fully custom aggregations in pandas groupby. This lesson builds a complete, production-ready sales analytics summary using apply, agg, and transform together.
18 min read