Making Data Simple

Amy discusses data analysis and models used in the science of fires


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Abstract

Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.


This week on Making Data Simple, we have Amy McDermott. Amy is a science journalist at Front Matter, the magazine section of PNAS (Proceedings of the National Academy of Sciences), where she covers new and emerging research. Her background spans ecology and journalism: she has an MA in conservation biology from Columbia University and a graduate certificate from the UC Santa Cruz Science Communication Program.


 Show Notes
4:20 - Amy’s background

7:25 – Amy summaries the stories on fires

11:21 – What does the data suggest about fires?

12:04 – Are there computer models on fires? 

17:35 – Real world example of how models are used

19:44 – How accurate is the data?

24:25 - Examining the data

28:35 - How do you define success? 

29:55 – Amy’s passion 

Amy McDermott - LinkenIn

Front Matter 

 
 Connect with the Team
Producer Kate Brown - LinkedIn.
Producer Steve Templeton - LinkedIn.
Host Al Martin - LinkedIn and Twitter

Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

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Making Data SimpleBy IBM Big Data & Analytics Hub

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