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Abstract
Data discovery is the art of going beyond answering specific questions. Given the goals of the organisation and a clean and reliable dataset, the ‘data detective’ is at his or her best in formulating intriguing questions. This paper looks at a variety of ways to stimulate the creative analytics process through the study of anomalies, the employment of segmentation, the avoidance of cognitive bias, and sidestepping the confusion between correlation and causation. With this set of tools in hand, the analyst must then communicate insights clearly in order to become a change agent via data.
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Author's Biography
Jim Sterne sold business computers to companies that had never owned one in the 1980s, consulted and keynoted about online marketing in the 1990s, founded the Marketing Analytics Summit in 2002 and co-founded the Digital Analytics Association in 2004. He has written a number of books, including most recently, ‘Artificial Intelligence for Marketing: Practical Applications’. He is now helping companies get more value from data and helping small and medium-sized agencies achieve scale at speed.
Citation
Sterne, Jim (2015, July 29). Discovering discovery: Data discovery best practices. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 1, Issue 3. https://doi.org/10.69554/UODC4428.Publications LLP