{"id":22470,"date":"2020-11-27T11:12:03","date_gmt":"2020-11-27T11:12:03","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/101-data-science-quotes\/"},"modified":"2023-10-03T13:57:40","modified_gmt":"2023-10-03T13:57:40","slug":"101-data-science-quotes","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/101-data-science-quotes\/","title":{"rendered":"101 Data Science Quotes"},"content":{"rendered":"\t\t
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Powerful Quotes To Inspire Your Data Science Journey<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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We are living in a world of big data that is empowering businesses and organisations to make data-driven decisions. Data science has become a key and central technology for this information age and data scientists has been dubbed the sexiest job of the 21st century.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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In this article, I have compiled a large collection of inspirational quotes <\/a>on data science. Hopefully, these words of wisdom will bring perspectives and inspire your data science journey.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The quotes are categorised alphabetically. If you find that I am missing any data science quotes that you like please feel free to suggest in the responses.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.\u201d
\u2014 Aaron Levenstein<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIf you can\u2019t explain it simply, you don\u2019t understand it well enough.\u201d
\u2014 Albert Einstein<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIn the end you should only measure and look at the numbers that drive action, meaning that the data tells you what you should do next.\u201d
\u2014 Alexander Peiniger<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIt is very common to find that the data to support many of the business information needs is simply not available at the levels required, or that it is of such bad quality that it is impossible to use. Resolution of these types of issues often requires fundamental changes to business processes.\u201d
\u2014 Alison Newell<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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It\u2019s easy to lie with statistics It\u2019s hard to tell the truth without statistics.\u201d
\u2014 Andrejs Dunkels<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe world is one big data problem.\u201d
\u2014 Andrew McAfee<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cConsumer data will be the biggest differentiator in the next two to three years Whoever unlocks the reams of data and uses it strategically will win.\u201d
\u2014 Angela Ahrendts<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData levels all arguments.\u201d
\u2014 Anthony W. Richardson<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThat which cannot be measured cannot be proven.\u201d
\u2014 Anthony W. Richardson<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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[Sherlock Holmes:] \u201cI never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.\u201d
\u2014 Arthur Conan Doyle<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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[Sherlock Holmes:] \u201cThe temptation to form premature theories upon insufficient data is the bane of our profession.\u201d
\u2014 Arthur Conan Doyle<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWithout the hard little bits of marble which are called \u2018facts\u2019 or \u2018data\u2019 one cannot compose a mosaic; what matters, however, are not so much the individual bits, but the successive patterns into which you arrange them, then break them up and rearrange them.\u201d
\u2014 Arthur Koestler<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cHiding within those mounds of data is the knowledge that could change the life of a patient, or change the world.\u201d
\u2014 Atul Butte<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIn our world of Big Data, businesses are relying on data scientists to glean insight from their large, ever-expanding, diverse set of data \u2026 while many people think of data science as a profession, it\u2019s better to think of data science as a way of thinking, a way to extract insights using the scientific method.
\u2014 Bob E. Hayes<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cNo large, global, heterogeneous, multi-business- and product-line enterprise can ever hope to clean up all of its data \u2014 it\u2019s always a continuous journey. The key is knowing what data sources feed your BI applications and how confident you are about the accuracy of data coming from each source.\u201d
\u2014 Boris Evelson<<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cMaybe stories are just data with a soul.\u201d
\u2014 Bren\u00e9 Brown<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cEverybody has certain red flags they want to keep an eye on, and big data tools enable you to do that in fairly close to real time.\u201d
\u2014 Brian Loughman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe data speaks for itself. That\u2019s the easiest measure of success.\u201d
\u2014 Caitlin Smallwood<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cYou imagine a data set &amp; you salivate at just thinking about that data set.\u201d
\u2014 Caitlin Smallwood<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cDiscovering things about people through their data was a really a cool thing.
\u2014 Caitlin Smallwood<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe goal is to turn data into information, and information into insight.\u201d
\u2014 Carly Fiorina<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe goal is to turn data into information, and information into insight.\u201d
\u2014 Carly Fiorina<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWe have to learn to interrogate our data collection process, not just our algorithms.\u201d
\u2014 Cathy O\u2019Neil<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe best way to learn data science is to do data science.\u201d
\u2014 Chanin Nantasenamat<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cErrors using inadequate data are much less than those using no data at all.\u201d
\u2014 Charles Babbage<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData are just summaries of thousands of stories.\u201d
\u2014 Chip &amp; Dan Heath<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cBig data is at the foundation of all the megatrends that are happening today, from social to mobile to cloud to gaming.\u201d
\u2014 Chris Lynch<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe great thing about predictions is that you can be wrong.\u201d
\u2014 Chris Wiggins<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cLearning how to do data science is like learning to ski. You have to do it.\u201d
\u2014 Claudia Perlich<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData is the new oil.\u201d
\u2014 Clive Humby<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cDon\u2019t be buffaloed by experts and elites. Experts often possess more data than judgment. Elites can become so inbred that they produce hemophiliacs who bleed to death as soon as they are nicked by the real world.\u201d
\u2014 Colin Powell<\/p>\n

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\u201cData are becoming the new raw material of business.\u201d
\u2014 Craig Mundie<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData are becoming the new raw material of business.\u201d
\u2014 Craig Mundie<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAim for simplicity in Data Science. Real creativity won\u2019t make things more complex. Instead, it will simplify them.\u201d
\u2014 Damian Duffy Mingle<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIn Data Science if you want to help individuals, be empathetic and ask questions; that way, you can begin to understand their journey, too.\u201d
\u2014 Damian Duffy Mingle<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cBig data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it\u2026\u201d
\u2014 Dan Ariely<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cYou can have data without information, but you cannot have information without data.\u201d
\u2014 Daniel Keys Moran<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAs data scientists, our job is to extract signal from noise.\u201d
\u2014 Daniel Tunkelang<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cI\u2019ve come across several people that are collecting data just to collect because at some point in the future they might be able to get some valuable information out of it. The question is, is it worth doing that? Is it worth keeping that data and for how long? \u2026 You can\u2019t just store your data forever. It\u2019s not free to do, and it\u2019s a compounding problem.\u201d
\u2014 Dave McCrory<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cI like to think of data as the new soil, Get in and get your hands dirty.\u201d
\u2014 David McCandless<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe next Darwin is more likely to be a data wonk than a naturalist wandering through an exotic landscape.\u201d
\u2014 David Weinberger<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cArtificial intelligence is growing up fast, as are robots whose facial expressions can elicit empathy and make your mirror neurons quiver.\u201d
\u2014 Diane Ackerman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cDespite an awful lot of marketing hype, big data are here to stay and big data analytics (i.e. data science and statistics) will remain aids to human thinking and not replacements for it!\u201d
\u2014 Diego Kuonen<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWithout a systematic way to start and keep data clean, bad data will happen.\u201d
\u2014 Donato Diorio<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData that sit unused are no different from data that were never collected in the first place.\u201d
\u2014 Doug Fisher<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWith too little data, you won\u2019t be able to make any conclusions that you trust. With loads of data you will find relationships that aren\u2019t real\u2026 Big data isn\u2019t about bits, it\u2019s about talent.\u201d
\u2014 Douglas Merrill<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cBig data isn\u2019t about bits, it\u2019s about talent.\u201d
\u2014 Douglas Merrill<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThanks to big data, machines can now be programmed to the next thing right But only humans can do the next right thing.\u201d
\u2014 Dov Seidman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAbove all else, show the data.\u201d
\u2014 Edward R. Tufte<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cFor me, data science is a mix of three things: quantitative analysis (for the rigor necessary to understand your data), programming (so that you can process your data and act on your insights), and storytelling (to help others understand what the data means).\u201d
\u2014 Edwin Chen<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThere were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.\u201d
\u2014 Eric Schmidt<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData\u2019s just the world making noises at you.\u201d
\u2014 Erin Shellman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe most interesting types of data are those collected for one purpose and used for another.\u201d
\u2014 Erin Shellman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAs a data scientist, even if you don\u2019t have the domain expertise you can learn it, and can work on any problem that can be quantitatively described.\u201d
\u2014 Erin Shellman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIt\u2019s a basic, intuitive right, worthy of enshrinement: Citizens, not the corporations that stealthily track them, should own their own data.\u201d
\u2014 Franklin Foer<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWithout big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.\u201d
\u2014 Geoffrey Moore<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWithout big data, you are blind and deaf in the middle of a freeway.\u201d
\n\u2014 Geoffrey Moore<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAll models are wrong, but some are useful.\u201d
\u2014 George E. P. Box<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe most valuable commodity I know of is information.\u201d
\u2014 Gordon Gekko<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cGood Big Data teams will be very tolerant of \u201cfailure\u201d.
\u2014 Graham Oakes<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cContact data ages like fish not wine\u2026it gets worse as it gets older, not better.\u201d
\u2014 Gregg Thaler<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cYou can best learn data mining and data science by doing, so start analyzing data as soon as you can! However, don\u2019t forget to learn the theory, since you need a good statistical and machine learning foundation to understand what you are doing and to find real nuggets of value in the noise of big data.\u201d
\u2014 Gregory Piatetsky-Shapiro<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cI keep saying that the sexy job in the next 10 years will be statisticians, and I\u2019m not kidding.\u201d
\u2014 Hal Varian<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cLet the dataset change your mindset.\u201d
\u2014 Hans Rosling<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cA data scientist is someone who can obtain, scrub, explore, model, and interpret data, blending hacking, statistics, and machine learning. Data scientists not only are adept at working with data, but appreciate data itself as a first-class product.\u201d
\u2014 Hillary Mason<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData isn\u2019t information; information isn\u2019t knowledge; knowledge isn\u2019t wisdom.\u201d
\u2014 Ian Lowe<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cScientists do not collect data randomly and utterly comprehensively. The data they collect are only those that they consider *relevant* to some hypothesis or theory.\u201d
\u2014 J. David Lewis-Williams<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe era of Data Technology is here and it will surpass the Information Technology era. The DT era is about transparency, sharing of information and enabling others. Alibaba is excited about the possibilities of the DT era and how it can bring value to society.\u201d
\u2014 Jack Ma<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cBeing a data scientist is not only about data crunching. It\u2019s about understanding the business challenge, creating some valuable actionable insights to the data, and communicating their findings to the business.\u201d
\u2014 Jean-Paul Isson<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData really powers everything that we do.\u201d
\u2014 Jeff Weiner<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cPossessed is probably the right word. I often tell people, I don\u2019t want to necessarily be a data scientist. You just kind of are a data scientist. You just can\u2019t help but look at that data set and go, I feel like I need to look deeper. I feel like that\u2019s not the right fit.\u201d
\u2014 Jennifer Shin<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAbove all get obsessed about data.\u201d
\u2014 Jerry Yang<<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIf we have data, let\u2019s look at data If all we have are opinions, let\u2019s go with mine.\u201d
\u2014 Jim Barksdale<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData will talk if you\u2019re willing to listen to it.\u201d
\u2014 Jim Bergeson<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cLearning from data is virtually universally useful Master it and you will be welcomed anywhere.\u201d
\u2014 John Elde<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData scientists are kind of like the new Renaissance folks, because data science is inherently multidisciplinary.\u201d
\u2014 John Foreman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAlthough data can make a compelling case for something, data rarely create the emotions needed to spur people into action.\u201d
\u2014 John Maeda<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cIntuition becomes increasingly valuable in the new information society precisely because there is so much data.\u201d
\u2014 John Naisbitt<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cNo great marketing decisions have ever been made on qualitative data.\u201d
\u2014 John Sculley<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAn approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.\u201d
\u2014 John Tukey<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe greatest value of a picture is when it forces us to notice what we never expected to see.\u201d
\u2014 John Tukey<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThat\u2019s all data is. A gift from yesterday that you receive today to make tomorrow better.\u201d
\u2014 Jon Acuff<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.\u201d
\u2014 Josh Wills<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cOne person\u2019s data is another person\u2019s noise.\u201d
\u2014 K. C. Cole<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cGreat data scientists never assume they know something without in-depth analysis, they think in hypotheses which need to be either rejected or proved, and they ask a lot of questions, even if they are 99.9% sure they know the answer.\u201d
\u2014 Karolis Urbonas<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThere\u2019s a digital revolution taking place both in and out of government in favor of open-sourced data, innovation, and collaboration.\u201d
\u2014 Kathleen Sebelius<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe more I analyze field data the more I stand amazed at the work of the Creator.\u201d
\u2014 Kingsley Ofosu-Ampong<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201c Big Data<\/a> has moved beyond its original hype phase, and even beyond its concept phase, and is now entering the productization and monetization phase. Every organization that is collecting vast sums of data now see that as an asset to generate better outcomes: new discoveries, improved decisions, and innovative products.\u201d
\u2014 Kirk Borne<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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“Data that is loved tends to survive.\u201d
\u2014 Kurt Bollacker<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cDestroy your money, you can earn more. Destroy your data, your existence is erased.\u201d
\u2014 Kurt Seapoint<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWhen used correctly, data is not the enemy of Intuitive Creative Thinkers; it is a powerful friend.\u201d
\u2014 Leena Patel<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWe chose it because we deal with huge amounts of data. Besides, it sounds really cool.\u201d
\u2014 Larry Page<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWith data collection, \u2018the sooner the better\u2019 is always the best answer.\u201d
\u2014 Marissa Mayer<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cFacts are stubborn, but statistics are more pliable.\u201d
\u2014 Mark Twain<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData is like garbage. You\u2019d better know what you are going to do with it before you collect it.\u201d
\u2014 Mark Twain<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cMany believe that Big Data is over-hyped, but seeing the fantastic use cases popping up around the globe I would say Big Data is under-hyped! In the coming years, Big Data will revolutionize every industry unlike we have seen before!\u201d
\u2014Mark van Rijmenam<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe more the data banks record about each one of us, the less we exist.\u201d
\u2014 Marshall McLuhan<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cTheories come and go, but fundamental data always remain the same.\u201d
\u2014 Mary Leakey<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cBig data is really about big questions.\u201d
\u2014 Mat Young<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe world is now awash in data and we can see consumers in a lot clearer ways.\u201d
\u2014 Max Levchin<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe most significant idea for big data is that it allows you to see around corners and react.\u201d
\u2014 Michael Cavaretta<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cBig data is the renaissance of the nerd.\u201d
\u2014 Michael Karasick<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThink analytically, rigorously, and systematically about a business problem and come up with a solution that leverages the available data.\u201d
\u2014 Michael O\u2019Connell<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThings get done only if the data we gather can inform and inspire those in a position to make [a] difference.\u201d
\u2014 Michael Schmoker<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData analysts who don\u2019t organize their transformation pipelines often end up not being able to repeat their analyses, so the advice I would give to myself is the same advice often given to traditional scientists: make your experiments repeatable!\u201d
\u2014 Mike Driscoll<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAn e-business can\u2019t run without accurate data about its\u2019 customers and business partners, and that need is elevating data cleansing from an obscure, specialized technology to a core requirement for data warehousing, CRM and web-based commerce.
\u2014 Mike Faden<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cA better world won\u2019t come about simply because we use data; data has its dark underside.\u201d
\u2014 Mike Loukides<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.\u201d
\u2014 Mike Loukides<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cGetting information off the internet is like taking a drink from a firehose.\u201d
\u2014 Mitchell Kapor<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning\u2026. Data-driven predictions can succeed\u2015and they can fail. It is when we deny our role in the process that the odds of failure rise. Before we demand more of our data, we need to demand more of ourselves.\u201d
\u2014 Nate Silver<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cOn average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.\u201d
\u2014 Nate Silver<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAutodidacts \u2014 the self-taught, un-credentialed, data-passionate people \u2014 will come to play a significant role in many organizations\u2019 data science initiatives.\u201d
\u2014 Neil Raden<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData is the new science. Big Data holds the answers.\u201d
\u2014 Patrick Gelsinger<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe human side of analytics is the biggest challenge to implementing big data.\u201d
\u2014 Paul Gibbons<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWe are moving slowly into an era where Big Data is the starting point, not the end.\u201d
\u2014 Pearl Zhu<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cEvery second of every day, our senses bring in way too much data than we can possibly process in our brains.\u201d
\u2014 Peter Diamandis<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cUniversal law: data wants to be free.\u201d
\u2014 Peter F. Hamilton<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Data scientists are able to think of ways to use data to solve problems that otherwise would have been unsolved, or solved using only intuition.\u201d
\u2014 Peter Skomoroch<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cInformation is the oil of the 21st century, and analytics is the combustion engine.\u201d
\u2014 Peter Sondergaard<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cYou have got to have a combination of machine intelligence and human insight to do big data well.\u201d
\u2014 Ray Eitel-Porter<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cThe machine approach is essential, because the data is so massive, but you still need a skilled human to interpret what the science is telling you and figure out what it means in a business context.\u201d
\u2014 Ray Eitel-Porter<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cWhen we have all data online it will be great for humanity It is a prerequisite to solving many problems that humankind faces.\u201d
\u2014 Robert Cailliau with Tim Berners-Lee<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cSome of the best theorizing comes after collecting data because then you become aware of another reality.\u201d
\u2014 Robert J Shiller<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cTorture the data, and it will confess to anything.\u201d
\u2014 Ronald Coase<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cData and data science have a massive influence on everything we do\u2026The impact that data has and will have..continues to grow every day.\u201d
\u2014 Ronald van Loon<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\u201cAs available data becomes more complex and extensive, weaving it into a visualization that invites engagement, understanding and decision-making is a bigger challenge, with a bigger opportunity for payoff.\u201d
\u2014 Ryan Bell<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cEverything is going to be connected to cloud and data\u2026 All of this will be mediated by software.\u201d
\u2014 Satya Nadella<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cI kind of have to be a master of cleaning, extracting and trusting my data before I do anything with it.\u201d
\u2014 Scott Nicholson<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cBig data doesn\u2019t only involve dealing with large volumes of data; it\u2019s about handling the sum of the data.\u201d
\u2014 Scott Schlesinger<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cData beats emotion. Sean Rad, Founder of Ad.ly and CEO of Tinder
If data had mass, the Earth would be a black hole.\u201d
\u2014 Stephen Marsland<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cListening to the data is important\u2026 but so is experience and intuition. After all, what is intuition at its best but large amounts of data of all kinds filtered through a human brain rather than a math model?\u201d
\u2014 Steve Lohr<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cData, I think, is one of the most powerful mechanisms for telling stories I take a huge pile of data and I try to get it to tell stories.\u201d
\u2014 Steven Levitt<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cThe only thing sacred to a corporate scientist is their scientific data.\u201d
\u2014 Steven Magee<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cMost of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong.\u201d
\u2014 Suhail Doshi<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cData is useful. High-quality, well-understood, auditable data is priceless.\u201d
\u2014 Ted Friedman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cThe difference between a great [data scientist] and a good one is like the difference between lightning and a lightning bug.\u201d
\u2014 Thomas C. Redman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cAny organization \u2014 and any individual within it \u2014 that gets started early with big data can gain a significant competitive edge.\u201d
\u2014 Thomas H Davenport<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cEvery company has big data in its future and every company will eventually be in the data business.\u201d
\u2014 Thomas H Davenport<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cData Scientist: The Sexiest Job of the 21st Century.\u201d
\u2014 Thomas H Davenport and D J Patil<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cWhere there is data smoke, there is a business fire.\u201d
\u2014 Thomas Redman<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cData is a precious thing and will last longer than the systems themselves.\u201d
\u2014 Tim Berners-Lee<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cWe\u2019re entering a new world in which data may be more important than software.\u201d
\u2014 Tim O\u2019Reilly<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cWho has the data has the power.\u201d
\u2014 Tim O\u2019Reilly<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cThe data fabric is the next middleware.\u201d
\u2014 Todd Papaioannou<<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cWhat we have is a data glut.\u201d
\u2014 Vernon Vinge<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cNobody ever talks about motivation in learning. Data science is a broad and fuzzy field, which makes it hard to learn. Really hard. Without motivation, you\u2019ll end up stopping halfway through and believing you can\u2019t do it, when the fault isn\u2019t with you\u2015it\u2019s with the teaching. Take control of your learning by tailoring it to what you want to do, not the other way around.\u201d
\u2014 Vik Paruchuri<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cTalented data scientists leverage data that everybody sees; visionary data scientists leverage data that nobody sees.\u201d
\u2014 Vincent Granville<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cBig data will replace the need for 80% of all doctors.\u201d
\u2014 Vinod Khosla<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cBig data will spell the death of customer segmentation and force the marketer to understand each customer as an individual within 18 months or risk being left in the dust.\u201d
\u2014 Virginia M. (Ginni) Rometty<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cIt\u2019s amazing how much data is out there. The question is how do we put it in a form that\u2019s usable?\u201d
\u2014 William Clay Ford, Jr.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
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\u201cWithout data you\u2019re just another person with an opinion.\u201d
\u2014 William Edwards Deming<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cIn God we trust. All others must bring data.\u201d
\u2014 William Edwards Deming<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cMost of the knowledge in the world in the future is going to be extracted by machines and will reside in machines.\u201d
\u2014 Yann LeCun<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cKnowledge is some compilation of data that allows you to make decisions, and what we find today is that computers are making a lot of decisions automatically.\u201d
\u2014 Yann LeCun<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

\u201cKnowledge is some compilation of data that allows you to make decisions, and what we find today is that computers are making a lot of decisions automatically.\u201d
\u2014 Yann LeCun<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

This article compiled a large collection of inspirational quotes on data science. The quotes are categorised alphabetically. Hopefully, these words of wisdom will bring perspectives and inspire your data science journey.<\/p>\n","protected":false},"author":886,"featured_media":16904,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[183],"tags":[94,1066],"ppma_author":[3736],"class_list":["post-22470","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-ml","tag-data-science","tag-inspirational-quotes"],"authors":[{"term_id":3736,"user_id":886,"is_guest":0,"slug":"chanin-nantasenamat","display_name":"Chanin Nantasenamat","avatar_url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2020\/08\/Chanin-Nantasenamat-150x150.jpg","user_url":"http:\/\/www.mahidol.ac.th\/mueng\/","last_name":"Nantasenamat","first_name":"Chanin","job_title":"","description":"Chanin Nantasenamat is Associate Professor and Head, Center of Data Mining and Biomedical Informatics at Mahidol University, Thailand. He is also Founder of Data Professor YouTube Channel and Associate Editor at Frontiers in Pharmacology. Thought Leader on AI and ML Education, he was a Visiting Professor at Uppsala University, Lund University, University of California at Los Angeles as well as the California State University at Fullerton."}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22470","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/users\/886"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=22470"}],"version-history":[{"count":5,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22470\/revisions"}],"predecessor-version":[{"id":33186,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22470\/revisions\/33186"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/16904"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=22470"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=22470"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=22470"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=22470"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}