Skip to main content

Home/ Learning Analytics/ Group items tagged patterns

Rss Feed Group items tagged

Filter: All | Bookmarks | Topics Simple Middle
hansdezwart

NetMiner - Social Network Analysis Software - 1 views

www.netminer.com/...home_01.jsp

social network analysis visualization lak11 tools week2

shared by hansdezwart on 19 Jan 11 - Cached
  • hansdezwart on 19 Jan 11
     
    NetMiner is an innovative software tool for Exploratory Analysis and Visualization of Network Data. NetMiner allows you to explore your network data visually and interactively, and helps you to detect underlying patterns and structures of the network
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
1 - 3 of 3
Showing 20▼ items per page