Table Partitioning Strategies for Large Data Tables
A query scanning a billion rows to find last week’s data is doing unnecessary work. Here’s how table partitioning strategies fix that, and how to pick the right key.
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Data Deduplication Techniques for Messy Real Data
Two records for the same customer, entered slightly differently, don’t announce themselves as duplicates. Here’s how data deduplication techniques actually handle that, with a real project example.
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Random Seed Reproducibility in Machine Learning
A single random seed can make a model look better or worse than it really is. Here’s why random seed reproducibility matters more than one lucky training run.
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Supervised vs Unsupervised Learning: The Core Difference
Supervised vs unsupervised learning comes down to one question: does your data already have the answer attached? Here’s how each works, with real project examples.
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Blue-Green vs Canary Deployment for ML Models
A model that looked good offline can still fail in production. Here’s blue-green vs canary deployment, two ways to roll out a new model version safely.
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Data Observability vs Data Quality Testing: The Difference
A test catches a known rule violation. It won’t catch a table that quietly stopped updating. Here’s data observability vs data quality testing, and why both matter.
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Data Lineage in Data Engineering: Why It Matters
A wrong number on a dashboard raises a question: where did it come from? Here’s what data lineage in data engineering actually tracks, and how dbt provides it almost for free.
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Change Data Capture vs Batch ETL: How to Choose
Reprocessing a full table works until it doesn’t. Here’s change data capture vs batch ETL, when each is the right fit, and a real project example of batch done well.
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Window Functions vs Subqueries in SQL: When to Use Each
A running total or rank within a group used to mean a slow, hard-to-read subquery. Here’s window functions vs subqueries in SQL, and when each actually fits.
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Slowly Changing Dimensions: Type 1 vs Type 2
When a dimension attribute changes, do you overwrite it or keep history? Here’s slowly changing dimensions type 1 vs type 2, and why the choice affects historical reports.
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