Mu-Sigma Big Data Panel 2012.02.27 (socialdatalab@googlegroups.com)
Andreas Weigend (Google Docs)
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Participants
OLD
Shared whiteboard for
Big Data War Stories
Feb 8, 2012
1900 Greeting
● Dave Nielsen
1915 Data Alchemy
● Gam Dias
● David Needham
1930 Eight Rules for Big Data
1. Start with the problem, not with the data
2. Share data to get data
3. Align interests of all parties
4. Make it trivially easy for people to contribute, connect, collaborate
5. Base the equation of your business on customer centric metrics
6. Decompose the business into its “atoms”
7. Let people do what people are good at, and computers what computers are good at
8. Thou shalt not blame technology for barriers of institutions and society
● Which rules would you agree with? Disagree with? What is missing?
1945 DISCUSSION
Singularity U / exponential technologies: What really happened in the last years?.
● How do you define “Big Data”?
○ Several disciplines
○ Different
○ Is is about the tools?
● Is Big Data just the latest fad? (Pete)
○ Difference /
○ Tools
○ Cycletime
● Assume you had all the data in the world at your availability: What would you do to delight your customers?
○ Better matches
● Where has big data changed your business
○ What you measure, how you manage (“the equations of your business”)
○ Customer
2015 CASES
1. Mark Torrance (CTO at Rocketfuel)
2. Chuck Lam (Product and Entrepreneur)
3. Raj Venkat
4. Pete Warden (Geek)
● Give us one example of a big data project that was a success. What were the hurdles? How did you manage to overcome them?
● Tell us about one big data project you did that failed. Why did it fail?
● What excites you most in this area currently?
Q&A
● Education
○ What kind of person should become a data scientist?
■Be lazy, not amazing
○ What’s hard about big data?
■Processing time, painful environment
○ How do I learn the skills I need for big data?
■Problem
● Big data and real time
●
●
2100 SUMMARY
The world in 2012
● Data Revolution
○ Mindset
○ Economics of communication
● Deep implications for companies
○ E- / me- / we-business; social commerce
● Deep implications for society and individuals
○ Data ownership, monetization
○ Future of work
○ Future of dating
○ Identity
● Do you have any learnings or insights on how the myriad tools and technologies supporting Big Data could be made to fit in a large enterprise/IT centric ecosystem? (Raj)
● Is “data scientist” a good description of what you do? (Chuck)
● What new skills did you need to learn in the last few years to do your job? (Chuck)
TIMELINE
5:30 pm Meet in Raj’s office (Pete will arrive at 6pm)
- order of appearance?
6:30 pm Networking
7:00 pm Welcome - Dave Nielsen
7:15 pm "The Need for Data Scientists" by Gam Dias (First Retail) and David Needham (Walmart Labs) who will describe the need for data scientists, machine learning engineers, and other engineers willing to learn about scaling and big data.
7:45 pm Panel Presentations: Each panelist (see below) will have approximately 10 minutes to recount a real-life story about working with big data. Then we will encourage discussion and questioning from audience. Moderated by Dr. Andreas Weigend
9:00 pm Final Words
9:30 pm Drinks & Networking
Dr. Andreas Weigend (Moderator) directs the Social Data Lab at Stanford University. He was the chief scientist at Amazon, where he drove the customer-centric and measurement-focused culture that has been central to Amazon's success. Today Andreas speaks at top conferences around the globe, and most recently he shared his vision on the future of data at the United Nations. He's a great speaker who challenges and inspires his audiences.
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