“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.”

“If you can’t explain it simply, you don’t understand it well enough.”

“In 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.”

“It 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.”

“It’s easy to lie with statistics It’s hard to tell the truth without statistics.”

“The world is one big data problem.”

“Consumer 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.”

“Data levels all arguments.”

“That which cannot be measured cannot be proven.”

[Sherlock Holmes:] “I 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.”

[Sherlock Holmes:] “The temptation to form premature theories upon insufficient data is the bane of our profession.”

“Without the hard little bits of marble which are called ‘facts’ or ‘data’ 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.”

“Hiding within those mounds of data is the knowledge that could change the life of a patient, or change the world.”

“In our world of Big Data, businesses are relying on data scientists to glean insight from their large, ever-expanding, diverse set of data … while many people think of data science as a profession, it’s better to think of data science as a way of thinking, a way to extract insights using the scientific method.”

“No large, global, heterogeneous, multi-business- and product-line enterprise can ever hope to clean up all of its data — it’s 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.”

“Maybe stories are just data with a soul.”

“Everybody 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.”

“The data speaks for itself. That’s the easiest measure of success.”

“You imagine a data set & you salivate at just thinking about that data set.”

“Discovering things about people through their data was a really a cool thing.”

“The goal is to turn data into information, and information into insight.”

“We have to learn to interrogate our data collection process, not just our algorithms.”

“The best way to learn data science is to do data science.”

“Errors using inadequate data are much less than those using no data at all.”

“Data are just summaries of thousands of stories.”

“Big data is at the foundation of all the megatrends that are happening today, from social to mobile to cloud to gaming.”

“The great thing about predictions is that you can be wrong.”

“Learning how to do data science is like learning to ski. You have to do it.”

“Data is the new oil.”

“Don’t 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.”

“Data are becoming the new raw material of business.”

“Aim for simplicity in Data Science. Real creativity won’t make things more complex. Instead, it will simplify them.”

“In Data Science if you want to help individuals, be empathetic and ask questions; that way, you can begin to understand their journey, too.”

“Big 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…”

“We should teach the students, as well as executives, how to conduct experiments, how to examine data, and how to use these tools to make better decisions.”

“You can have data without information, but you cannot have information without data.”

“As data scientists, our job is to extract signal from noise.”

“I’ve 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? … You can’t just store your data forever. It’s not free to do, and it’s a compounding problem.”

“I like to think of data as the new soil, Get in and get your hands dirty.”

“The next Darwin is more likely to be a data wonk than a naturalist wandering through an exotic landscape.”

“Artificial intelligence is growing up fast, as are robots whose facial expressions can elicit empathy and make your mirror neurons quiver.”

“Despite 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!”

“Without a systematic way to start and keep data clean, bad data will happen.”

“Data that sit unused are no different from data that were never collected in the first place.”

“With too little data, you won’t be able to make any conclusions that you trust. With loads of data you will find relationships that aren’t real… Big data isn’t about bits, it’s about talent.”

“Big data isn’t about bits, it’s about talent.”

“Thanks to big data, machines can now be programmed to the next thing right But only humans can do the next right thing.”

“Above all else, show the data.”

“For 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).”

“There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days.”

“Data’s just the world making noises at you.”

“The most interesting types of data are those collected for one purpose and used for another.”

“As a data scientist, even if you don’t have the domain expertise you can learn it, and can work on any problem that can be quantitatively described.”

“It’s a basic, intuitive right, worthy of enshrinement: Citizens, not the corporations that stealthily track them, should own their own data.”

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

“Without big data, you are blind and deaf in the middle of a freeway.”

“All models are wrong, but some are useful.”

“The most valuable commodity I know of is information.”

“Good Big Data teams will be very tolerant of “failure”.

“Contact data ages like fish not wine…it gets worse as it gets older, not better.”

“You can best learn data mining and data science by doing, so start analyzing data as soon as you can! However, don’t 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.”

“I keep saying that the sexy job in the next 10 years will be statisticians, and I’m not kidding.”

“Let the dataset change your mindset.”

“A 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.”

“Data isn’t information; information isn’t knowledge; knowledge isn’t wisdom.”

“Scientists do not collect data randomly and utterly comprehensively. The data they collect are only those that they consider relevant to some hypothesis or theory.”

“The 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.”

“Being a data scientist is not only about data crunching. It’s about understanding the business challenge, creating some valuable actionable insights to the data, and communicating their findings to the business.”

“Data really powers everything that we do.”

“Possessed is probably the right word. I often tell people, I don’t want to necessarily be a data scientist. You just kind of are a data scientist. You just can’t help but look at that data set and go, I feel like I need to look deeper. I feel like that’s not the right fit.”

“Above all get obsessed about data.”

If we have data, let’s look at data If all we have are opinions, let’s go with mine.”

“Data will talk if you’re willing to listen to it.”

“AI is good at describing the world as it is today with all of its biases, but it does not know how the world should be.”

“Learning from data is virtually universally useful Master it and you will be welcomed anywhere.”

“Data scientists are kind of like the new Renaissance folks, because data science is inherently multidisciplinary.”

“Although data can make a compelling case for something, data rarely create the emotions needed to spur people into action.”

“Intuition becomes increasingly valuable in the new information society precisely because there is so much data.”

“No great marketing decisions have ever been made on qualitative data.”

“An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.”

“The greatest value of a picture is when it forces us to notice what we never expected to see.”

“That’s all data is. A gift from yesterday that you receive today to make tomorrow better.”

“Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.”

“One person’s data is another person’s noise.”

“Great 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.”

“There’s a digital revolution taking place both in and out of government in favor of open-sourced data, innovation, and collaboration.”

“The more I analyze field data the more I stand amazed at the work of the Creator.”

“Big Data 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.”

“Data that is loved tends to survive.”

“Destroy your money, you can earn more. Destroy your data, your existence is erased.”

“We chose it because we deal with huge amounts of data. Besides, it sounds really cool.”

“When used correctly, data is not the enemy of Intuitive Creative Thinkers; it is a powerful friend.”

“With data collection, ‘the sooner the better’ is always the best answer.”

“This is not going to be less people in IT. I frankly believe there will actually be more people in IT, but more people in IT working on a different set of tasks…Everyone needs a boss, including bots.”

“Facts are stubborn, but statistics are more pliable.”
— Mark Twain

“Data is like garbage. You’d better know what you are going to do with it before you collect it.”

“Many 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!”

“The more the data banks record about each one of us, the less we exist.”

“Theories come and go, but fundamental data always remain the same.”

“Big data is really about big questions.”

“The world is now awash in data and we can see consumers in a lot clearer ways.”

“The most significant idea for big data is that it allows you to see around corners and react.”

“Big data is the renaissance of the nerd.”

“Think analytically, rigorously, and systematically about a business problem and come up with a solution that leverages the available data.”

“Things get done only if the data we gather can inform and inspire those in a position to make [a] difference.”

“Data analysts who don’t 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!”

“An e-business can’t run without accurate data about its’ 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.”

“A better world won’t come about simply because we use data; data has its dark underside.”

“Data scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.”

“Getting information off the internet is like taking a drink from a firehose.”

“The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning…. Data-driven predictions can succeed―and 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.”

“On average, people should be more skeptical when they see numbers. They should be more willing to play around with the data themselves.”

“Autodidacts — the self-taught, un-credentialed, data-passionate people — will come to play a significant role in many organizations’ data science initiatives.”

—

“Data is the new science. Big Data holds the answers.”

“The human side of analytics is the biggest challenge to implementing big data.”

“We are moving slowly into an era where Big Data is the starting point, not the end.”

“Every second of every day, our senses bring in way too much data than we can possibly process in our brains.”

“Universal law: data wants to be free.”

“[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.”

“Information is the oil of the 21st century, and analytics is the combustion engine.”

—

“You have got to have a combination of machine intelligence and human insight to do big data well.”

“The 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.”

“When we have all data online it will be great for humanity It is a prerequisite to solving many problems that humankind faces.”

“Some of the best theorizing comes after collecting data because then you become aware of another reality.”

“Torture the data, and it will confess to anything.”

“Data and data science have a massive influence on everything we do…The impact that data has and will have..continues to grow every day.”

“As 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.”

“Everything is going to be connected to cloud and data… All of this will be mediated by software.”

“I kind of have to be a master of cleaning, extracting and trusting my data before I do anything with it.”

“Big data doesn’t only involve dealing with large volumes of data; it’s about handling the sum of the data.”

“Data beats emotion.”

“If data had mass, the Earth would be a black hole.”

“Listening to the data is important… 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?”

“Data, 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.”

“The only thing sacred to a corporate scientist is their scientific data.”

“Most of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong.”

“Data is useful. High-quality, well-understood, auditable data is priceless.”

“The difference between a great [data scientist] and a good one is like the difference between lightning and a lightning bug.”

“Any organization — and any individual within it — that gets started early with big data can gain a significant competitive edge.”

“Every company has big data in its future and every company will eventually be in the data business.”

“Data Scientist: The Sexiest Job of the 21st Century.”

“Where there is data smoke, there is a business fire.”

“Data is a precious thing and will last longer than the systems themselves.”

“We’re entering a new world in which data may be more important than software.”

“Who has the data has the power.”

“The data fabric is the next middleware.”

—

“What we have is a data glut.”

“Nobody 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’ll end up stopping halfway through and believing you can’t do it, when the fault isn’t with you―it’s with the teaching. Take control of your learning by tailoring it to what you want to do, not the other way around.”

“Talented data scientists leverage data that everybody sees; visionary data scientists leverage data that nobody sees.”

“Big data will replace the need for 80% of all doctors.”

“Big 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.”

“It’s amazing how much data is out there. The question is how do we put it in a form that’s usable?”

“Without data you’re just another person with an opinion.”

“In God we trust. All others must bring data.”

—

“Most of the knowledge in the world in the future is going to be extracted by machines and will reside in machines.”

“Knowledge 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.”

—