Data Science & Data in Society

Data Science & Data in Society

1. Lesson form the Data Analysis Handbook

   • Communication Skills are underrated
   • The biggest Challenge
     • Collection
     • Wrangling
   • Data Sceintis is Better at Statistic than a Software Engginer
   • A Data Sceintist is better at software. engineering than a statistician
   • Data Science is still nascent
   • The roles is less well defined
   • Keep curious with data
     • Quality is as important as the technical ability

2. Cloud Technology

   • Advantages
     • Distributed computing
     • Personalised Services
   • Disadvanatages
     • Security & Privacy Breaches
       • Access Misuse

3. Roles of Intenet in the development of DS

   • the first big users of data science were internet giants
   • source of data for use
   • avenue for data science tools

4. The Scientifict Methods

   • Algorithm
     • Observation
     • Ask a Question
     • Form a Hypothesis
     • Conduct Experiment
     • Collect Data
     • Decision
       • accept hypothesis
       • Reject Hypothesis
   • The Problem
   • The Theory Fate
     • The end of theory
       • The quest of knowledge used to begin with grand theories. Now it begins with massive amounts of data. Wlecome to the Petabyte Age
     • Not the end of theory
       • Massimo Pigliuci
         • Science is not about finding patterns. Its about finding explanation for those patterns
       • Drew Conway
         • In some areas the data does not exist
       • Andrew Gelman
         • correlation is not causation

5. Futurology

   • Process
     • Digitisation
       • Turning analog/manual into atomated, machine driven, computer and digital platform
     • Datafication
       • Turn everything into data
   • Example
     • Car Evolution
   • Driven by
     • Innovation
     • Globalisation