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Data Analytics Quotes

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Data Analytics Quotes

“Blogging, writing conventional articles, and being science consultant and pocket protector ninja to various web portals and TV programs, quite often trying to promote the penicillin of hard data to people who had no interest in being cured of their ignorance.”

“Using this technique, Baum et al constructed a forest that contained 1,000 decision trees and looked at 84 co-variates that may have been influencing patients' response or lack of response to the intensive lifestyle modifications program. These variables included a family history of diabetes, muscle cramps in legs and feet, a history of emphysema, kidney disease, amputation, dry skin, loud snoring, marital status, social functioning, hemoglobin A1c, self-reported health, and numerous other characteristics that researchers rarely if ever consider when doing a subgroup analysis. The random forest analysis also allowed the investigators to look at how numerous variables *interact* in multiple combinations to impact clinical outcomes. The Look AHEAD subgroup analyses looked at only 3 possible variables and only one at a time. In the final analysis, Baum et al. discovered that intensive lifestyle modification averted cardiovascular events for two subgroups, patients with HbA1c 6.8% or higher (poorly managed diabetes) and patients with well-controlled diabetes (Hba1c < 6.8%) and good self-reported health. That finding applied to 85% of the entire patient population studied. On the other hand, the remaining 15% who had controlled diabetes but poor self-reported general health responded negatively to the lifestyle modification regimen. The negative and positive responders cancelled each other out in the initial statistical analysis, falsely concluding that lifestyle modification was useless. The Baum et al. re-analysis lends further support to the belief that a one-size-fits-all approach to medicine is inadequate to address all the individualistic responses that patients have to treatment.”

“I believe the technological industry is switching in a different direction that one may think in the Metaverse. Why spend trillions of dollars on big data when it is becoming more useless? We need dynamic content to create a boom in the tech industry for the next millennium. Why hire someone with a 4 year degree from college for a career in database administration when companies can't afford to pay 100k a year? We can manage it quite fine in google sheets or excel. The utilization of AI will then completely defeat the purpose of Data As A Service when a program can dynamically build hash objects in random access memory by simply using a small script like (via switch) while creating a [5th XYZ Stargate] just like the Diablo version, but with a smaller seed. You could then store those objects for the blockchain Inna virtualized file container ;)." - Jonathan Roy Mckinney”