Why data quality matters when working with data at scale
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Data quality has always been an afterthought. Teams spend months instrumenting a feature, building pipelines, and standing up dashboards, and only when a stakeholder flags a suspicious number does anyone ask whether the underlying data is actually correct. By that point, the cost of fixing it has multiplied several times over. This is not a […]
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This story continues at The Next Web
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