Preventing, Diagnosing, and Curing Bad Data

Businesses use insights to drive the decision-making process and create innovative products. But those can only be as good as the quality of the data they were extracted from. Inaccuracies or biases can result in costly mistakes with the potential to cause long-term harm to a company’s reputation, growth, and revenue. A structured, consistent manner to approaching data quality issues is vital to prevent having to solve more expensive problems later. Aligning these efforts early and with intention is the best way a company can ensure healthy data-informed outcomes. In this talk, Shailvi Wakhlu uses her 16 years of experience in tech and team leadership to guide you through the data lifecycle and help you pinpoint where low-quality data can sneak in. Her framework for preventing, diagnosing, and fixing issues is easy to follow and apply across various businesses.