Big Data: A Revolution That Will Transform How We Live, Work, and Think explores the significant changes that will come along with big data. The book talks about the revolutions from many different perspectives, including what big data is, why big data makes significant differences and how we can face the new challenge. The following are some interesting viewpoints:
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- Causal or Correlation? Mayer-Schönberger and Cukier talk about moving away from the causal approach in big data era. They think “predictions based on correlations lie at the heart of big data. “ With so much data around and more to come, correlation analysis is more practical. Hypotheses are no longer crucial for correlation analysis. Their viewpoints include:
- Causal analyis assumes that we know. However, we should let data speak, and it will reveal something we don't know.
- Causal is used when data is related small. When large data set is available, correction is more important.
- The causal approach has difficulty handling exceptions.
- Causal analysis needs to control experiments that are costly and time-consuming.
- Big data has the dark side. We have to see the dark side of big, stay in control and "guard against overreliance on data".
"Data is platform" -Tom O'Reilly
“The IT revolution is evident all around us, but the emphasis has mostly been on the T, the technology. It is time to recast our gaze to focus on the I, the information.”