Download: Big Data Revolution Transform Think eBook (ePub, KINDLE, PDF) + Audio Version

  • File Size: 2137 KB
  • Print Length: 257 pages
  • Publisher: Eamon Dolan/Houghton Mifflin Harcourt; Reprint edition (March 5, 2013)
  • Publication Date: March 5, 2013
  • Language: English

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Mcdougal clearly has a excellent deal of insight since to how data have been viewed in the previous. He also generally gives into focus for the lay person how information will be managed, handled and used in typically the future. In which level typically the book can be quite interesting. In a different level, a single of readability and keeping one's interest, I identified the book to fewer compelling. The author tends to make a point and after that repeats and repeats the same point across several chapters..... ok, I get it. The particular text feels a bit like a lecture within places which doesn't ensure that the readability. If you have a specific fascination with typically the whole concept of 'big data' this book will be worth wading into but it may be a few slow sledding from moment to time., Big Data should be read by anyone who clicks on the screen, moves a mouse or carries a smartphone. Yes, that means basically everybody. Why? Because existence usually are being dissected and handled with a level of intrusion and manipulation that even a classic corporate DIE BAHN data vet like myself ( I used to be online to be able to IBM's central systems within NY from my COMPUTER at home in Arlington, TX, in 1984 ) finds frightening.

The guide offers a scary overview into how your information and my data becomes gobbled up, warehoused, sold and resold in the way that it will be very unlikely each of us will be permitted any privacy that may be honestly protected. Presently there are good and bad components of this tidal trend. It could help put out fires in many areas of our lives - treatments, urban planning, marketing usefulness, quality of life, etc. - and drowning us all at the base of a world where typically the root aim of our life is not as crucial as what is " trending" on Twitter. Unfortunately, typically the solutions proposed by typically the authors to protect us as a countervailing pressure ( " human agency" ) against this threat in response to the data tsunami fall far short of a reliable answer. Any time you find out about their self-policing recommendation to be ushered within by the data accumulators and industry experts with integrity, please go ahead and super impose over that hype the formerly glossy image of firms just like Arthur Anderson (mother ship to Accenture) that were supposed to be watchdogs accountable for detecting and subjecting accounting malfeasance but right now are dead and gone at the bottom from the cesspool of professional criminals.

The most troubling factor of the book's check out of the global information landscape lies in giving credence to " correlation" over " causation. " What this boils straight down to telling the basic public, " We're throwing away the compass used by Western Civilization for the couple of thousand a number of forgetting true North. The way of the future is far better decided because they are able to be able to predict which way typically the wind blows. " ( My quote ). This path of expediency arises boldly as the final recommendation with a naive promise that society will certainly then use the forecasts to correct problems that bedevil us now since we mere humans usually are too silly (pandering to be able to dull-witted conclusions characterized within examples from old BB coaches in the film Moneyball ) and losing time trying to decide ultimate root causes. The particular data displays us just what we cannot find out.

Allow me contrast with that viewpoint an example of why causation still dominates supreme over the valuable power of " N=all" information bases. If numbers were the best answer to fixing problems rather than root trigger analysis why is that that the USA has not necessarily solved the " benign neglect" collateral damage of our national welfare system that Sen. Daniel Tanker Moynihan warned the country regarding in 1969 as technology wonk in DC? We all have more than sufficient data to verify his warning being prescient within the over 40 12 months backwash of statistics chronicling the break down of black family structures. Still, the data is not necessarily correcting outcomes like typically the 70% of black youngsters born without a dad in the family. BIG DATA won't slow straight down the wave of problems eroding our cultural shores unless we, as people, deal with the root causes honestly and forcefully.

We should all be mindful of how BIG DATA could end up being a surfer's guide to be able to staying ahead of typically the waves until everything failures in to the rocky shore waiting for us. Understand and deal with it now, if all of us can., The key problem with this book is how it treats the partnership between theory and scientific research. The authors claim that using big information is different as a result of small data (? ) or sampled data within that there is zero need for theories or even hypotheses since the first is functioning on a universe instead of a sample. Drilling down will be easier and more informative. Etc. But clearly the just way to interpret any type of data is against the theory about what issues and why. The authors mention the differences in between correlation and causation, but this comes near typically the end of the guide after much foolishness regarding the advantages of big information. The best part of the guide is about what businesses and governments performing with big data and how that might be a bit of a problem from your perspective of privacy plus civil liberties. One factoid that I found interesting is that Google used textual content data from the deciphering of library books to be able to improve its translation software program. There was a very good discourse on the use of online search behavior with regard to tracking potential epidemics. Furthermore an interesting story about how the city of New York was able to use large data to predict manhole cover explosions. In typically the end, though, this guide is absolutely just a component of the general buzz about big data rather than a serious contribution to be able to the larger discussion that is still emerging.

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