Does our understanding of data bias our analytics outcomes?

This is a podcast episode titled, Does our understanding of data bias our analytics outcomes?. The summary for this episode is: <p>Why do some data-driven decisions seem to go so disastrously wrong? Ironically, the answer to this question likely isn’t found in the data at all, but rather our subconscious. In a time when companies have never been more data rich, it’s often our inherent information biases that doom critical analytics and data science work.</p> <p>Is it possible to take the bias out of data work? That’s the question we ponder in this episode featuring Ciaran Dynes, chief product officer at Matillion.</p> <p>This episode will also cover:</p> <ul> <li>What responsibilities companies and people have to curb information bias</li> <li>How hypothesis testing and experimentation can improve data work</li> <li>What’s the most egregious example of information bias in the wild?</li> </ul>