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You've probably heard how big data has changed the world by bringing hyper-customization to the forefront, discovering obscure patterns, and allowing people to react quickly to new information. In this episode Leina discusses the pros and cons of the big data revolution from a scientific standpoint. Here are the pitfalls she wants you to be aware of:   Big data analysis finds complex patterns quickly but cannot explain scientific phenomena. Most people are willing to accept subjective explanations to phenomena regardless of whether it is supported by evidence. Research and analyses using big data is shaped around the data that is available, while the underlying causal relationship may not be captured.By emphasizing correlations rather than root-causes we further impede finding effective long-term solutions. "Correlation is not causation" is used selectively to confirm biases or enable cognitive dissonance. It is true, but observing patterns is part of the process of asking questions.Big data is inherently dehumanizing by turning people into numbers. Data fishing, also known as significance chasing, is when one approaches a research problem without a predefined hypothesis.  There is an increasing absence of gold standard research methodology that emphasizes the use of sample randomization, placebo groups, and blinding to minimize bias. Big data quality is notoriously poor. Missing data, subjective and inconsistent definitions, and unstandardized methods of collection make the data scientist's job difficult. Qualitative methods are not always taken into consideration to confirm or reject big data findings. Any data can be skewed and omit information altogether. Standardization is likely impossible. It should be emphasized that one should always READ THE FINE PRINT. Leina is here to remind you that bigger is not always better. Join on Facebook, Twitter, and Instagram https://linktr.ee/leinacast

Internet Of Things, like many technologies, is 10:1 hype to the peasants. Massive IOT networks are toys for the big boys. When will massive networks fall in your lap, and what will it look like?