Of Building Data Products


  • [Update 5/9/15] Lots of good pointers from “Everything We Wish We’d Known About Building Data Products
    • Data Products Need to Be Built Differently
    • Keep Your data clean
    • Give Data Back in a Powerful Way – But don’t confuse or overwhelm the users
      • The users have to feel safe
      • The users have to feel they are in control
    • Never try to launch a complicated data product on a fixed schedule
  • [Update 11/28/13] Notes from blog by Jon “Data Driven Disruption at Shuttershock” on what a data products company is
    1. Data is your product, regardless of what you sell
    2. Data is your lens into your business – Jon echo’s Peter’s insights viz. invest in data access; feel the pulse of the business & iterate
    3. Data creates your growth
  • Back to the main feature, Peter’s talk
  • A very insightful & informative talk by Peter Skomoroch of Linkedin via Zipfian academy
  • It is short & succinct, only 37 minutes. I urge all to watch
  • The slides of the talk “Developing Data Products” are at slideshare
  • Quick Notes:
    • A Data Product understands the world through inferential probabilistic models built on data
      • So collecting right data through “thoughtful” data design is very important
      • The data determines & precedes the feature set & the intelligence of your app
        • LinkedIn is a prime example – as they get more data, the app has become more intelligent, intuitive and ultimately more useful
        • Offer progressively sophisticated products, leveraging the data & insights, across the different user population segments – customer segmentation & stratification is not just for retail !
    • While more data, see “Unreasonable Effectiveness of Data” Distinguished Lecture by Peter Norvig, is good; for complex models, a deep understanding of the models and feature engineering would eventually be necessary (beyond the “black box”)
      • Data products about people, are usually complex, in terms of models as well as the data

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[Update 12/13/13] Remember, a data product usually has the three layers – Interface, Inference & Intelligence

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2 thoughts on “Of Building Data Products

  1. Pingback: Big Data on the other side of the Trough of Disillusionment | My missives

  2. Pingback: The Curious Case of the Data Scientist Profession | My missives

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