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Explore the critical importance of data quality in industrial projects through this insightful conference talk. Discover how bad data is costing the US economy trillions of dollars and contributing to the failure of many Data Science projects. Learn from high-profile case studies, including Microsoft's Tay.ai twitter-bot, to understand the consequences of neglecting data cleansing. Gain valuable insights into techniques for fixing bad data, tailored for intermediate-level Data Science professionals. Delve into the reality of industrial projects, where the majority of time is spent working with data, and understand how the largest improvements in performance often come from enhancing the underlying data quality.
