OAS BIG DATA TALENTS and Tecnologas Transformadoras BLOCKCHAIN
OAS BIG DATA, TALENTS and Tecnologías Transformadoras BLOCKCHAIN FIFTH MEETING OF MINISTERS AND HIGH LEVEL AUTHORITIES ON SCIENCE AND TECHNOLOGY Prof. Jose Luis Guerrero Cusumano Georgetown University Business School Est. , M. S. Stat, Ph. D. Eng. , Dr. h. c. Adm. guerrerj@georgetown. edu (also in Linked. In) MEDELLIN, COLOMBIA, NOV 2 2017
Big Data The National Institute of Standards and Technology (NIST) Big Data refers to the inability of traditional data approaches to efficiently handle the new datasets. Characteristics of Big Data are as follows: (NIST , 2017) • Volume (i. e. , the size of the dataset); • Variety (i. e. , data from multiple repositories, domains, or types); • Velocity (i. e. , rate of flow); and • Variability (i. e. , the change in structure). https: //bigdatawg. nist. gov/show_Input. Doc. php
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A new Paradigm Traditional Approach Big Data Approach Structured & Repeatable Analysis Iterative & Exploratory Analysis Business Users Determine what question to ask IT Delivers a platform to enable creative discovery IT Business Structures the data to answer that question Explores what questions could be asked Monthly sales reports Profitability analysis Customer surveys Brand sentiment Product strategy Maximum asset utilization Source: Martin Pavlík, IBM Big Data Platform Overview , IBM corporation, January 2013
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“Big data” Big Data Feelings http: //www. ocdqblog. com/home/fear-replaced-apathy-as-enemy-of-data Now Fearful Few Many and growing Apathetic Vast majority Many, but fewer Truly Excited 6 2010 A few, Still relatively few, mostly in the but growing, and not data space just those in the data space Eagle Creek fire, a 31, 000 -acre blaze burning near Portland, Oregon, encroached on the nearby Beacon Rock Golf Course
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The Fourth Industrial Revolution Source: The Future of Jobs. World Economic Forum, 2017
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Looking for Talent Jobs that did not exist 10 years ago • • App Developer Social Media Manager Data Scientist Driverless car engineer Cloud computing specialist Sustainability Manager You. Tube content creators Drone Operators Companies struggle to bridge the data talent gap • Another familiar trend this year is the ever-growing struggle to find and retain analytical talent. • Lucker points to the 2015 MIT Sloan Management Review, which found that 40 percent of companies struggle with finding the talent they need. • Colleges and universities are working hard to produce data science talent, but the number of data scientists will remain limited and the competition for top talent will be fierce. • "Companies need to recognize that they need to really develop close relationships with these degree programs, " https: //www. cio. com/article/3025869/analytics/6 -analytics-trends-that-will-shape-business-in-2016. html 10
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GAFA: Google, Apple, Facebook, Amazon more than half of Americans believe the four giants that comprise GAFA. (Google, Apple, Facebook and Amazon) have become an integral part of our society. 13
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Respondents who thought the tipping points (shifts) would occur Over 800 executives and experts from the technology sector, the survey asked respondents for their perception of when these tipping points or shifts would occur, Source: Deep Shift Technology Tipping Points and Societal Impact, WORLD ECONOMIC FORUM, 2015 – 17
WHAT IS A BLOCKCHAIN: the steam engine, the electric motor and Blockchain RADICAL AND DISRUPTIVE INNOVATION • A blockchain is an implementation of cryptographic technology that enables data to be shared across a network of computers controlled by multiple organizations and individuals. • Blockchain can serve as a registry, inventory system, and transaction platform for recording, tracking, monitoring, and transferring rights to different asset classes, including intellectual property, votes, digital identity, health data, and real estate. Source: Deep Shift Technology Tipping Points and Societal Impact, WORLD ECONOMIC FORUM, 2015 – 18
Big Data Challenges But big data has its challenges, which include 1. control, 2. data authenticity and 3. monetization. • First, who controls the infrastructure when there are multiple actors involved? • Second, how well can you trust the data? • Third: How do you monetize the data? 19 Source: Blockchains for Big Data, From Data Audit Trails to a Universal Data Exchange, Trent Mc. Conaghy, Nov 17, 2017
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SMALL DATA REVOLUTION • Small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks. 21
22 • 200 people with diabetes in one of the state's FROM THEORY INTO PRACTICE poorest regions, the Mississippi Delta, will be given Internet-capable computer tablets loaded with software provided by Intel-GE Care Innovations and GE Healthcare. • Each patient will be given a baseline exam and a treatment program, which will require them to check glucose levels two to four times daily using a home-testing kit. The results will be transmitted to medical teams at both hospitals using Bluetooth technology. Patients will also check their weight and blood pressure daily and transmit the information. • At the University of Mississippi, the medical team will include a dietician, a pharmacist, an ophthalmologist, an endocrinologist, a diabetes education expert and a nurse practitioner, who will work with local medical providers at Sunflower Medical Center to provide a full range of specialty care for patients as needed.
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Big Data Challenges • Second, how well can you trust the data? For example: • If you generate the data yourself, how do you prove you were the originator? If you get data from others, how do you know it was truly them? • What about crashes and malicious behavior? Machines crash, glitches happen, bits flip. Zombie Io. T toasters might be inputting garbage. So after all your fancy Spark calculations, is it still just garbage out? • Third: How do you monetize the data? For example: • How do you transfer the rights of the data, or buy rights from others? • There’s a long standing dream of a universal data marketplace; how? 24 Source: Blockchains for Big Data, From Data Audit Trails to a Universal Data Exchange, Trent Mc. Conaghy, Nov 17, 2017
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What is a Smart City • Quite simply, smart cities use Internet of Things (Io. T) devices such as connected sensors, lights, and meters to collect and analyze data. • The cities then use this data to improve infrastructure, public utilities and services, and more. http: //www. businessinsider. com/internet-of-things-smartcities-2016 -10
ISO 37120 - Sustainable development of communities -- Indicators for city services and quality of life ISO 37120 standard on city indicators – how they help city leaders set tangible targets, including service quality and quality of life The indicators included in ISO 37120: 2014 will help cities – assess their performance – measure progress overtime – ultimate goal of improving quality of life and sustainability The standard’s uniform approach will enable cities to seamlessly compare where they stand in relation to other cities. This information can in turn be used to identify best practice and learn from one another
The SMART CITY standard: Dissecting ISO 37120 Sl No. Title 1 The long road to zero waste cities Solid waste collection & its recycling. 2 Economic indicators in the new smart city standard City’s unemployment rate and population living in poverty. 3 Why education may be the most important smart city indicator of all? Female school-aged population enrolled in school, students completing primary education & secondary education, student/teacher ratio. 4 Does your city's air quality measure up to the new smart city standard? Particulate matter (PM 2. 5 - PM 10) concentration and Greenhouse gas emissions measured in tonnes per capita. 5 How debt, spending and tax collections add up in new smart city standard? Debt service ratio. 6 Fire and emergency response Number of firefighters, fire related deaths and natural indicators -- how safe is your city? disaster related deaths. Source: Smart Cities Council 03 Oct, 2014 Core Indicators …. to be continued 28
The SMART CITY standard: Dissecting ISO 37120 Sl No. Title Core Indicators 7 How voting, women and corruption figure in the smart city standard Voter participation in last municipal election and Women as a percentage of total elected to city-level office. 8 How healthy is your city? Average life expectancy, no. of in-patient hospital beds & no. of physicians, mortality rate. 9 How fun is YOUR city? None 10 How safe is your city? Number of police officers & homicides. 11 The homeless challenge cities face City population living in slums. 12 What the new smart city standard says about energy? Residential electrical use per capita (k. Wh / year), city population with authorized electrical service, energy consumption of public buildings per year (k. Wh / m 2) and energy derived from renewable sources. 29 Source: Smart Cities Council 03 Oct, 2014
How Cities Can Use ISO 371 20 1. Assess service performance and quality of life 2. Prioritize city budgets 3. Improve operational transparency 4. Benchmark regionally and globally 5. Support open data and applications 6. Leverage public and private funding for infrastructure investments http: //smartcitiescouncil. com/article/dissecting-iso-37120 -why-new-smart-city-standard-good-news-cities
A Smart City, as a “system of systems”, can potentially generate vast amounts of data, especially as cities install more sensors, gain access to data from sources such as mobile devices, and government and other agencies make more data accessible. Consequently, Big Data techniques and concepts are highly relevant to the future of Smart Cities.
The WCCD certified its first Foundation Cities including Amman, Amsterdam , Barcelona, Boston, Bogota, Buenos Aires, Dubai, Guadalajara , Haiphong, Helsinki, Johannesburg, London, Los Angeles, Makkah, Makati, Minna, Melbourne, Rotterdam, Shanghai, and Toronto. We are now inviting cities of all sizes to join this global initiative and to become certified under ISO 37120.
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