Designing Event Data for Product Analytics
Design event contracts that keep product metrics interpretable as identifiers, client clocks, delivery retries, and application versions change.
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ETL, ELT, and Data-Pipeline Design Patterns
ETL and ELT differ in where the transformation runs. The patterns underneath them decide whether a pipeline can be rerun without breaking anything.
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Batch, Micro-Batch, and Streaming
Choose processing modes from freshness needs, then test how late events, duplicates, and recovery affect the results.
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Data Modeling for OLTP and OLAP Systems
How row meaning, identity, dependencies, aggregation, and time shape operational and analytical data models.
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Designing End-to-End Data Architecture
How consumer requirements determine data contracts, logical layers, physical deployment, consistency boundaries, and recovery decisions.