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Knowledge Content LibraryDecisions, Artificial Intelligence, and Data QualityThomas Redman, "the Data Doc", Data Quality Solutions Abstract: We all know the drill, "garbage in, garbage out,” "decisions are no better than the quality of data used to make them” etc….. But few managers trust their data and in turn revert to their intuitions. It is tempting to seek relief in machine learning. But the quality of data an algorithm uses is no better than that used by managers and lacks intuitions. This presentation provides a, get the basics right overview of data quality for decision makers and machine learning practitioners. It will cover the broad range of requirements, including "is this the right data?” and "is the data right?” It will highlight the pros and cons of the most common approaches for addressing data quality and describe the organizational imperatives for making the needed improvements at scale. Finally, the presentation explores the more stringent requirements that using data in AI brings and what to do about them.
Click on the file below to hear a sample of the presentation. SDP membership is required for access to this webinar. Keywords: analysis and modeling anamod, artificial intelligence artint, machine learning machlearn, value of information valoi, | ||
