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DATA PRODUCTS (5 Broad Groups of Data Products FUNCTIONS (:one: Raw Data…

- - - - can purchase domain specific raw data from government
      - google history?
      - ESRI demographic data
        
        Updated regularly, Esri Demographics datasets are of high value Integrate datasets into your workflows by consuming them as maps, charts, infographics, reports, and more.
  - - - We could, in the case of customer data, add additional attributes like assigning a customer segment to each customer
      - we could add their likelihood of clicking on an ad or of buying a product from a certain category.
    - - DOSM sells data with statistics input
      - Statista, statistic portal
  - - - Behind the scenes, the product extracts features, classifies the image and matches it to stored images, returning the ones that are most similar.
  - - - user in control to interpret the data, and to make decision to act or otherwise
      - we have taken design-decisions in data collection, derivation of new data, in choosing what data to display and how to display it
    - - Google Analytics, that could mean changing the editorial strategy, addressing leaks in the conversion funnel, or doubling down on a given product strategy.
      - WAZE?
        
        it computes back end the best route in different time frame for a given trip set by users
  - - - e.g.
        
        Netflix product recommendations
        
        Spotify’s Discover Weekly
        
        Self-driving cars or automated drones are more physical manifestations of this closed decision-loop
    - - sometimes with an explanation as to why the AI chose that option, other times completely opaque
  - - - Data that's collected without asking the user for it, via some other means. Also called “implicit data.
      - e.g.
        
        user browser
        
        timestamp in fb message conversation
    - - Data you need to request from a user. The user needs to actively provide this data. Also called “explicit data.
- - - - Data Science Services
      - Data Science Training
        
        Andrew Ng. Coursera
      - Data Science Communities
        
        Anthony Goldbloom, Kaggle
      - Data Products
        
        Christian Chabot, Tableu
        
        Arun C Murthy, Hortonworks
- - - - DATA product
        
        Google Analytics
        
        ts primary objective is bringing a quantitative understanding of online behaviour to the user. Here data is central to the interaction with the user and unlike the other products mentioned
      - INFORMATION product
        
        Google Search
        
        a service to search information
    - - Data Science produce insights
        
        insights are most useful, the best when it is actionable
        
        data products are built upon core analytics
      - application of models
        
        usually, domain specific dataset
        
        predictive model
        
        e.g.
        
        Recommender system
        
        e.g. Amazon, Youtube, social tags, online news, WAZE
        
        2 more items...
        
        a subclass of information filtering systems that are meant to predict the preferences or ratings that a user would give to a product
        
        inferential model
      - DS workflow O'Reilly
    - - derives value from data & produces more data & therefore more value
      - a cycle of data contributes value, value creates data
    - - sleep better, better diet etc.
      - :+1: data products provide deeply personalized experiences
- - - - Hence, Data increasingly affects every aspect of our lives
    - - internet & connectivity creates surplus of DATA material
        
        transform us all as
        
        data producers
        
        data consumers
- - - - from large dataset
      - to help make predictions
      - build different types of models
        
        fall into different types of categories