Economic Implications of Data Science: Past, Present and Future. Patrick Harrington, Ph.D. Co-Founder & Chief Data Scientist compgenome.
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1 Economic Implications of Data Science: Past, Present and Future Patrick Harrington, Ph.D. Co-Founder & Chief Data Scientist compgenome.com
2 Data Science Related Programs at University of Michigan Statistics Applied Math Complex Systems Mathematics School of Information Operations Research Computer Science Data Science Physics Bioinformatics Biostatistics Applied Physics Electrical Engineering
3 Every two days now we create as much information as we did from the dawn of civilization up until 2003 Eric Schmidt, Google
4 Paradigm of Modern Big Data and Data Science Measurement The ability to listen in, often in real time, at any point in any complex system at the most granular level Computation/Storage Distributed computation over a potential real time massive data signal Highly available, fault tolerant storage for applications to be built on top Complex System, e.g., Ad Targeting of Individuals Control/Optimization Optimality: The ability to optimize global objective functions via optimizing/ controlling sum of the parts at most granular level
5 Timeline of Important Milestones in Evolution of Modern Data Science Time Comp Genome Founded Oracle Buys BlueKai Monsanto Buys Climate Corp RocketFuel IPO PayPal Buys BrainTree Nevada Legalizes Driverless Cars Workday IPO Apace Hadoop LinkedIn IPO Wealthfront Founded Uber Founded Airbnb Founded Netflix Streaming Google Big Table Twitter Founded Compressive Sensing Google IPO Facebook Founded The Elements of Statistical Learning Initial Sequencing of Human Genome Amazon IPO LASSO publication
6 Thematic Evolution of Big Data and the Positioning of Modern Data Science to be Front and Center in Every Business Real Time Distributed PubSub/Compute Distributed Storage Map Reduce Data Science in Internet Tech Cheap Cloud Solutions
7 2015 Sector Market Dynamics: Vector Space Representation Trending Up Mature On Demand: Housing On Demand: Transportation Payments Physical Retail Self Driving Cars Health-Care Financial Tech People (HR 2.0) Precision Agriculture Synthetic Biology Immature (Opportunity) Ad/Marketing Tech e-commerce Social Trending Down
8 "The best minds of my generation are thinking about how to make people click ads. Jeff Hammerbacher
9 Building Blocks of Promising New Business Ventures in Big Data/Data Science Core Product/Business Enabled by: Data Science, Optimization, & Control New Data Signal Generated Existing, Inefficient Problem Domain or Market Multi-Source, Aggregated Data
10
11 The unobservable market force that helps the demand and supply of goods in a free market to reach equilibrium automatically is the invisible hand.
12 Network Representation of Labor Market Google Pinterest Amazon Uber Counsyl Microsoft Employee
13 University of Michigan BS in CS Student University of Michigan PhD in Statistics Student Name Hidden for Talk Name Hidden for Talk
14 Measurement Understand at individual level people s compensation Extract featured tied to individual and other market participants, e.g., companies, universities, etc. Computation Control/Optimization Unsupervised: Who you are most like and should be comparing self to market Supervised: Explain variation in compensation between economic sectors to high-dimensional user signal Reverse engineer the invisible hand of this currently inefficient market Enable every labor market participant to understand their position on a financial efficient frontier and how to increase that location towards high compensation
15 2015 Sector Market Dynamics: Vector Space Representation Trending Up Mature On Demand: Housing On Demand: Transportation Payments Physical Retail Self Driving Cars Health-Care Financial Tech People (HR 2.0) Precision Agriculture Synthetic Biology Immature (Opportunity) Ad/Marketing Tech e-commerce Social Trending Down
16 "The best minds of my generation are thinking about how to make people click ads live better lives.
17 Thank You.
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