Too BIG to Ignore…

I was reading this book which argues the business case for big data written by Phil Simon. Some tidbits:

At high level Big Data allows organizations to do 3 things:

  1. Better (if not completely) understand the past (i.e. what has happened & why)
  2. Better (if not completely) understand the present  (i.e. what has happening & why)
  3. Better (if not completely) understand the future (i.e. what will happen & why)

Data 101 and the Data Deluge:

A best quote from Tim Berners Lee surmises the whole idea on this: – Any enterprise CEO really ought to be able to ask a question that involves connecting data across the organization, be able to run a company effectively, and especially to be able to respond to unexpected events. Most organizations are missing this ability to connect all the data together. There’s lot of data disconnect and companies are unable to make informed decisions.

Demystifying Big data: It’s

  • already here
  • extremely fragmented
  • a complement not a substitute
  • can yield better predictions
  • neither omniscient nor precise
  • generally wide not long
  • dynamic and largely unpredictable
  • largely consumer driven
  • external and unmanageable in traditional sense
  • inherently in complete
  • overlapping with BI & Data Mining
  • democratic

Big Data Techniques: 

  • A/B testing
  • Association Rule Learning
  • Classification
  • Cluster Analysis
  • Collaborative Filtering
  • Crowdsourcing
  • Data Fusion & Integration
  • Data Mining
  • Ensemble Learning
  • Genetic Algorithms
  • Machine Learning
  • Natural language Processing
  • Neural Networks
  • Pattern Recognition
  • Predictive Modeling
  • Regression, RFID & NFC Data Identification & Tagging
  • Sentimental Analysis
  • Signal Processing
  • Supervise and Unsupervised Learning
  • Simulation, text Analysis
  • Time Series Analysis, and
  • Visualization
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