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hansdezwart

Insurers Test Data Profiles to Identify Risky Clients - WSJ.com - 0 views

online.wsj.com/...4648604575620750998072986.html

insurance profiling lak11 week1 datamining

shared by hansdezwart on 12 Jan 11 - No Cached
  • hansdezwart on 12 Jan 11
     
    Life insurers are testing an intensely personal new use for the vast dossiers of data being amassed about Americans: predicting people's longevity.
Vanessa Vaile

LAK11: Big Data Small Data « Viplav Baxi's Meanderings - 0 views

learnos.wordpress.com/...lak11-big-data-small-data

data lak11 analytics week2 tools connectivism #lak11 #evomlit education

shared by Vanessa Vaile on 23 Jan 11 - No Cached
  • which data is more appropriate - BIG or small
  • most discussion about big data centres on quantity
  • other elements you mention – implication, new models, new decision making approaches – all flow from this abundance of data.
  • ...15 more annotations...
  • Increased data quantity requires new approaches
  • Is small beautiful? Look at the following links. Big Data, Small Data New Age of Innovation (Prahalad) So you like Big Data
  • reading on Insurers and the work done by Levitt and Dubner on Freakonomics tells us clearly that data not earlier thought relevant or causal can be an efficient predictor.
  • Secondly, strategies designed on BIG data
  • may overpower small data strategies
  • Thirdly, BIG data also has BIG impacting factors.
  • Fourthly, actions taken on BIG data will have big consequences,
  • Lastly, if everybody, big or small, started using BIG analytics, to make decisions
  • companies would anyway lose the competitive differentiator that analytics brings to them.
  • Corresponding to the question, how big does BIG need to be, the question I have is - how small really is small.
  • defining patterns that emerge from very small pieces of data (e.g. synchronicity)
  • how tools for SNA and analysis of BIG data can apply to Learning and Knowledge Analytics
  • at the other end it embraces how small changes can cause long term variations
  • not easy to analyze the small data
  • data that is small enough not to be generalizable
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