#64 Intersections of Analytics, AI, Linguistics and Culture with Prashant Natarajan – Principal, AI & Analytics

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Prashant Natarajan has 18+ years’ experience in building EMRs, ERP, big data platforms, actionable analytics, and machine/deep learning applications. Before joining Deloitte, he served in hands-on global consulting and product leadership roles at H2O.ai, Oracle, McKesson Payer Solutions, Healthways, and Siemens. Prashant is Co-Faculty Instructor of Data Science and AI at Stanford University School of Medicine, Palo Alto, CA, USA. He volunteers as an industry expert and guest lecturer at leading Australian universities. Prashant serves as an industry advisor at the CIAPM computer vision project in University of California San Francisco, Council for Affordable Health Coverage, and Pistoia Alliance Center for Excellence in Artificial Intelligence.  

In this episode, Prashant describes how essential human interaction is for success. In a technology-heavy space, human interaction and linguistics were not very common. Instead of complaining about it, Prashant went and got his masters to focus on English in the technology space. To have success, we need a clear understanding of culture. Culture is language, and language at its core is mathematics. How do we interact with people to figure out what their strengths are? Prashant considers himself the luckiest person on earth to have the experiences he has had in his career. 

Then, Prashant discusses how to identify business problems and integrate it with data science. Data analytics is as old as when humans started interacting with each other. By nature, all human beings are data analytics, consuming creatures. Historically, the application of computing data and analysis have been humans trying to define a problem, find data to solve the problem, and then writing algorithms that will create insights. Prashant is a massive admirer of the human mind and the human brain, which is far superior to any artificial machine. When it comes to AI, computing can do things that the human mind cannot. Business leaders must look at data science as a way to help them define business problems, rather than purely using deduction. Later, Prashant advises companies moving into data-driven products, explains horizontal capabilities, and the use of machine learning in healthcare. 

Enjoy the show!

We speak about:

  • [01:25] How Prashant started in the data space 

  • [03:45] Studying communications and linguistics  

  • [08:45] Mentoring young professionals  

  • [11:45] Work with people who are smarter than you  

  • [15:00] Merging business problems with data science  

  • [19:45] The value business leaders see in data  

  • [25:00] Advice for companies who are moving into data-driven products

  • [29:45] What excites Prashant about the future of data 

  • [34:05] Horizontal capabilities 

  • [37:20] The use of machine learning in healthcare  

  • [44:20] Improving product development 

  • [48:40] Prashant’s proudest moment

  • [50:15] The manufacturing industry 

  • [52:20] We learn more from our failures than our successes 


Prashant’s LinkedIn: https://www.linkedin.com/in/natarpr/

Demystifying Big Data and Machine Learning for Healthcare (Himss Book)


  • “Human interaction is the most key determiner of success or not.”

  • “Today, we have the technology that has caught up with the human need.”

  • “Data science is increasingly a horizontal capability that will impact all of us.”

  • “I celebrate relationships because they allow me to learn.”

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Prashant Natarajan is based in Melbourne, Victoria, Australia.

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!

#30 Aaron Black - Chief Data Officer

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Aaron started his career working in accounting and building management information systems (MIS). He had his own company, worked in multiple industries and then got into biology and genomics. Today he is the Chief Data Officer at the Inova Translational Medicine Institute.

We speak about:

* How to take research into scaled applications

* The importance of sharing your knowledge and helping others understand

* Why you're only as good as your team members

* How to engage many different types of stakeholders

* Challenges of data management in healthcare

* Data governance & provenance in healthcare

* Data monetization & it's stigma in healthcare

* The benefits of data sharing consortiums

* The potential of genomic & DNA data

* Handling algorithm biases

* Enabling reproducible research through data

* Why "perfection is the enemy of good"

* The importance of creating & sharing your mental models


Weapons of Math Destruction




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Aaron is based in Washington DC Metro Area, USA

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!