We dive into critical topics like achieving consistency and consensus across distributed data, managing concurrency through transactions and isolation levels, and processing massive datasets with both batch frameworks like MapReduce and modern stream processing tools. Along the way, we discuss the role of data models, storage engines, schema evolution, and even the ethical dimensions of data collection. Whether you’re architecting large-scale systems or just curious about the mechanics behind them, this episode will sharpen your understanding of the data backbone that powers today’s technology.

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