The Library · Insights
Deep dives across data, automation & AI
982 in-depth articles — from Excel foundations to production machine learning. Filter by topic or difficulty to find exactly what you need.
Power QueryExpert
Building Custom Connectors in Power Query: Extending Data Source Support with the M SDK
Learn to build production-grade Power Query custom connectors from scratch using the M SDK. This deep-dive lesson covers OAuth 2.0 authentication, navigation tables, pagination, schema enforcement, and distribution — everything a real connector needs.
28 min read
Career DevelopmentPractitioner
Building a Data Freelance Service Tier Menu: How to Structure Bronze, Silver, and Gold Packages That Upsell Clients Without Hourly Negotiation
Hourly pricing turns every client conversation into a negotiation about time instead of value. This lesson shows you how to build a tiered Bronze, Silver, and Gold package menu that lets clients self-select, anchors proposals on outcomes, and creates a natural upsell path — no awkward rate discussions required.
20 min read
Career DevelopmentPractitioner
Decoding the Data Job Description: How to Identify Real Requirements, Red Flags, and Your Actual Fit
Most data job descriptions are a mess of contradictory requirements, wishful thinking, and corporate boilerplate — and if you read them at face value, you'll either never apply or end up in the wrong role. This lesson gives you a systematic framework for identifying what a data job actually requires, spotting dysfunction before it costs you months of your career, and assessing your real fit using weight-adjusted analysis instead of checkbox anxiety.
24 min read
Data EngineeringPractitioner
Monitoring dbt Pipeline Failures in Production: Alerting, Logging, and Root Cause Analysis with Elementary and re_data
Silent data failures are more dangerous than loud ones — your pipeline runs green while bad data flows to your dashboards. Learn how to instrument dbt with Elementary and re_data for anomaly detection, Slack alerting, and systematic root cause analysis in production environments.
22 min read
Data EngineeringPractitioner
Implementing Dead Letter Queues and Poison Message Handling in Data Pipelines
Most data pipelines eventually encounter a message they can't process — and without a strategy for handling it, one bad payload can bring down your entire consumer. This lesson walks you through building a complete dead letter queue system with Python: failure classification, enriched routing, replay pipelines, and production monitoring.
21 min read
AI & Machine LearningPractitioner
Contextual Compression in RAG: Filtering and Compressing Retrieved Chunks Before Passing to the LLM
Raw vector search retrieves the right documents but passes too much noise to your LLM. This lesson teaches you how to build compression pipelines that strip retrieved chunks down to only what's actually relevant to the query — reducing token costs and improving answer quality at the same time.
23 min read
AI & Machine LearningPractitioner
Multimodal LLM Integration: Processing Images, PDFs, and Documents with Vision APIs
Text-only LLMs can't handle scanned receipts, chart-heavy reports, or complex PDF tables — but multimodal models can. Learn how to build a production document intelligence pipeline that routes, processes, and extracts structured data from any document type using vision APIs, with full cost and accuracy control.
24 min read
AI & Machine LearningPractitioner
Few-Shot and Zero-Shot Prompting: When and How to Use Examples to Improve AI Output Quality
Most AI prompts underperform because they rely on instructions when they should be using examples. This lesson teaches you the mechanics of few-shot prompting, how to design example sets strategically, and how to debug the most common failure modes — with complete, production-ready prompts for data workflows.
20 min read
SQLPractitioner
Lateral Joins and CROSS APPLY: Row-by-Row Subquery Power in SQL
Standard SQL joins can't reference the current outer row inside a subquery — lateral joins and CROSS APPLY break that limitation wide open. Learn how they work, when to use them, and how to write them for real-world data transformation problems across PostgreSQL, SQL Server, MySQL, and BigQuery.
23 min read
Power AutomatePractitioner
Handling Pagination and Throttling When Querying Large Datasets in Power Automate
Most Power Automate flows silently return incomplete data because they don't handle pagination — or they crash against API rate limits with no recovery. This lesson teaches you how pagination and throttling actually work, and how to build production-grade flows that retrieve complete datasets reliably.
21 min read
Power AppsPractitioner
Power Apps Collections and Local Data Management: Mastering ClearCollect, Patch, and In-Memory Data Operations
Most Power Apps developers only scratch the surface of collections. This lesson teaches you how to architect a full local data management layer — using ClearCollect, Patch, UpdateIf, and SaveData — to build offline-capable, batch-submitting, production-grade Canvas Apps. Includes a complete hands-on inspection app exercise.
19 min read
Power BIPractitioner
Implementing Power BI Aggregations to Optimize Query Performance on Billion-Row Enterprise Datasets
Slow DirectQuery dashboards on massive fact tables aren't a hardware problem — they're an architecture problem. This lesson walks you through building a complete Power BI aggregation layer that routes common analytical queries to fast in-memory pre-summaries while preserving drill-through access to full granular detail.
21 min read