Sharon Lin has big aspirations when it comes to big data. Sharon wants to apply data science to solve California’s mega drought problem by integrating real-time weather data into crop irrigation systems. Additionally, she wants to use advanced image recognition algorithms to predict, track, and monitor endangered wildlife migration patterns to help endangered species from being hunted.
I sat down with Sharon this week to talk about applications of data science in the field of mobile behavioral analytics. Over the last 5 years, Sharon has worked in the emerging field of mobile behavioral analytics and she shared some golden nuggets with me.
Here’s what I picked up:
- Mobile analytics and its relationship with evolution and emergence of IoT (internet of things)
- Privacy, Personalization, and IoT: Sharon shared her brief thoughts on the intersection of these areas.
- Two main problems most companies face to fully maximize their data potential, and what to do about it!
- Difference between data processing engines Spark and Hadoop
Connect with Sharon on her LinkedIn https://www.linkedin.com/in/sharonxlin or email her at “sharonxlin” at “gmail.com”
Podcast (click the play button):
About Sharon Lin:
Sharon started off her undergrad study at UC Berkeley majoring in Architecture. Her grandfather was an architect, so she got interested in architecture at a very young age. Sharon is a huge sports fan and she reads a lot of sports analytics articles to analyze the players’ strength/weakness and that’s how she was introduced to the field of statistics and data analytics If Sharon wasn’t planning to go into nonprofit, she would likely go into sports analytics.
DataLeaders.io YouTube show: