At Coinbase we pride ourselves in Efficient Execution. In software engineering, a common manifestation of this principle is DRY — don’t repeat yourself. For example, we might consolidate logic into a single service or library. But I’m a Data Scientist on our Data Team where our core role is to help derive value from Coinbase’s data in the form of analytics, data visualization, causal inference, modeling, and more. In this context DRY means something a bit different. By applying DRY to the process of creating value from data, we shift our focus from ad-hoc question-answering and toward maintaining a single semantic view of the data that describes our business, enabling efficient, consistent, and automated value generation.
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