Inspirational Data Quotes

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

We often hesitate to follow our intuition out of fear. Most usually, we are afraid of the changes in our own life that our actions will bring. Intuitive guidance, however, is all about change. It is energetic data ripe with the potential to influence the rest of the world. To fear change but to crave intuitive clarity is like fearing the cold, dark night while pouring water on the fire that lights your cave. An insight the size of a mustard seed is powerful enough to bring down a mountain-sized illusion that may be holding our lives together. Truth strikes without mercy. We fear our intuitions because we fear the transformational power within our revelations.

In the business people with expertise, experience and evidence will make more profitable decisions than people with instinct, intuition and imagination.

Faith doesn't rely on odds or statistical data. God only requires that we have faith; the rest is up to him.

Market research gives you enough time to learn from your competitors’ mistakes, take inspiration from their strengths, and exploit their weaknesses.

Interviews are a qualitative form of collecting data. The reason it generates good responses is because it’s way more personal than other forms of data gathering techniques.

Data that comes subliminally and is acted upon will look like luck or inspiration.

We need data and we need discernment.

It's not man versus machine; it's man with machine versus man without. Data and intuition are like horse and rider, and you don't try to outrun a horse; you ride it.

To save wildlife and wild places the traction has to come not from the regurgitation of bad-news data but from the poets, prophets, preachers, professors, and presidents who have always dared to inspire.

Ratios matter in Data Science. Dreams should be big and worries small.

If we knew what is already there, there will be no need for research.

You can’t manage what you can’t measure” is a maxim that is taught and believed by many in both the business and education sectors. But in fact, the phrase is ridiculous—something said by people who are unaware of how much is hidden. A large portion of what we manage can’t be measured, and not realizing this has unintended consequences. The problem comes when people think that data paints a full picture, leading them to ignore what they can’t see. Here’s my approach: Measure what you can, evaluate what you measure, and appreciate that you cannot measure the vast majority of what you do. And at least every once in a while, make time to take a step back and think about what you are doing.

If you want to know how a manager is performing ask to see their data, really want to know... ask those that report to them.

Anthropological data clearly showed that cultures practicing religions historically had outlived nonreligious cultures. Fear of being judged by an omniscient deity always helps inspire benevolent behavior.

Historically, pandemics have forced humans to break with the past and imagine their world anew. This one is no different. It is a portal, a gateway between one world and the next. We can choose to walk through it, dragging the carcasses of our prejudice and hatred, our avarice, our data banks and dead ideas, our dead rivers and smoky skies behind us. Or we can walk through lightly, with little luggage, ready to imagine another world. And ready to fight for it.

People who stand out in work and life possess the power to get what they want and inspire others while doing so.

Recognizing that two points of data are connected is not enough. The System must ask why one point affects another.

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

It’s only because the data force us into corners that we are inspired to create the highly counterintuitive structures that form the basis for modern physics.

Sometimes, it is not you who finds good ideas when you are seeking them. Instead, good ideas find you in the most unexpected circumstances.

It is in the combination of words and visuals that the magic of understanding often happens.

There were no laptops or handheld devices in class. Ilgauskas didn't exclude them; we did, sort of, unspokenly. Some of us could barely complete a thought without touch pads or scroll buttons, but we understood that high-speed data systems did not belong here. They were an assault on the environment, which was defined by length, width, and depth, with time drawn out, computed in heartbeats.

Tu stii ca nu-i nici o fericire sa vezi ce-i inlauntrul omului, pentru ca nici acolo, nici in afara lui lucrurile nu sunt asezate o data pentru totdeauna si se schimba pana sa apuci sa spui ce si cum.

Every day your mind will receive data both good and bad. You have the power to keep the good and delete the bad. Get rid of the negative thoughts in your mind and you will rid yourself of the negativity in you.

To summarize, these are the four critical contributions you need to bring to your team: deep knowledge (1) of your customer, (2) of the data, (3) of your business and its stakeholders, and (4) of your market and industry.

When you’re trying to communicate a big, audacious concept, it’s helpful to remember that where data falls short, a story might close the gap, and where story alone is not persuasive enough, data can make up the difference.

they didn't examine the problem and accumulate data to figure out the best solution - they engineered the outcome they wanted from the beginning. if they didn't achieve their desired outcome, they understood it was because of a decision they made at the start of a process

More often than not, at the end of the day (or a month, or a year), you realize that your initial idea was wrong, and you have to try something else. These are the moments of frustration and despair. You feel that you have wasted an enormous amount of time, with nothing to show for it. This is hard to stomach. But you can never give up. You go back to the drawing board, you analyze more data, you learn from your previous mistakes, you try to come up with a better idea. And every once in a while, suddenly, your idea starts to work. It's as if you had spent a fruitless day surfing, when you finally catch a wave: you try to hold on to it and ride it for as long as possible. At moments like this, you have to free your imagination and let the wave take you as far as it can. Even if the idea sounds totally crazy at first.

These examples should be models for communication, precisely because they inspire curiosity. “How does money influence politics?” is not an especially engaging question, but “If I were running for president, how would I raise lots of money with few conditions and no scrutiny?” is much more intriguing.

In the name of speed, Morse and Vail had realized that they could save strokes by reserving the shorter sequences of dots and dashes for the most common letters. But which letters would be used most often? Little was known about the alphabet’s statistics. In search of data on the letters’ relative frequencies, Vail was inspired to visit the local newspaper office in Morristown, New Jersey, and look over the type cases. He found a stock of twelve thousand E’s, nine thousand T’s, and only two hundred Z’s. He and Morse rearranged the alphabet accordingly. They had originally used dash-dash-dot to represent T, the second most common letter; now they promoted T to a single dash, thus saving telegraph operators uncountable billions of key taps in the world to come. Long afterward, information theorists calculated that they had come within 15 percent of an optimal arrangement for telegraphing English text.

Good teams get their inspiration and product ideas from their vision and objectives, from observing customers' struggle, from analyzing the data customers generate from using their product, and from constantly seeking to apply new technology to solve real problems. Bad teams gather requirements from sales and customers.

Google had a built-in disadvantage in the social networking sweepstakes. It was happy to gather information about the intricate web of personal and professional connections known as the “social graph” (a term favored by Facebook’s Mark Zuckerberg) and integrate that data as signals in its search engine. But the basic premise of social networking—that a personal recommendation from a friend was more valuable than all of human wisdom, as represented by Google Search—was viewed with horror at Google. Page and Brin had started Google on the premise that the algorithm would provide the only answer. Yet there was evidence to the contrary. One day a Googler, Joe Kraus, was looking for an anniversary gift for his wife. He typed “Sixth Wedding Anniversary Gift Ideas” into Google, but beyond learning that the traditional gift involved either candy or iron, he didn’t see anything creative or inspired. So he decided to change his status message on Google Talk, a line of text seen by his contacts who used Gmail, to “Need ideas for sixth anniversary gift—candy ideas anyone?” Within a few hours, he got several amazing suggestions, including one from a colleague in Europe who pointed him to an artist and baker whose medium was cake and candy. (It turned out that Marissa Mayer was an investor in the company.) It was a sobering revelation for Kraus that sometimes your friends could trump algorithmic search.

I eventually realized that to make a difference I had to step outside, into creation, and refocus on the roots of my passion. If an ounce of soil, a sparrow, or an acre of forest is to remain then we must all push things forward. To save wildlife and wild places the traction has to come not from the regurgitation of bad-news data but from the poets, prophets, preachers, professors, and presidents who have always dared to inspire. Heart and mind cannot be exclusive of one another in the fight to save anything. To help others understand nature is to make it breathe like some giant: a revolving, evolving, celestial being with ecosystems acting as organs and the living things within those places -- humans included -- as cells vital to its survival.

Habit Testing.” It is a process inspired by the build-measure-learn methodology championed by the lean startup movement. Habit Testing offers insights and actionable data to inform the design of habit-forming products. It helps clarify who your devotees are, what parts of your product are habit-forming (if any), and why those aspects of your product are changing user behavior.

The platforms, designed to accommodate and harvest infinite data, inspired an infinite scroll. They encouraged a cultural impulse to fill all spare time with someone else’s thoughts. The internet was a collective howl, an outlet for everyone to prove that they mattered. The full spectrum of human emotion infused social platforms. Grief, joy, anxiety, mundanity flowed. People were saying nothing, and saying it all the time. Strangers swapped confidences with other strangers in return for unaccredited psychological advice. They shared stories of private infidelities and public incontinence; photos of their bedroom interiors; photos, faded and cherished, of long-dead family members; photos of their miscarriages. People were giving themselves away at every opportunity.

To understand this first event, you need to know that we rely on Unix and Linux machines to store the thousands of computer files that comprise all the shots of any given film. And on those machines, there is a command—/bin/rm -r -f *—that removes everything on the file system as fast as it can. Hearing that, you can probably anticipate what’s coming: Somehow, by accident, someone used this command on the drives where the Toy Story 2 files were kept. Not just some of the files, either. All of the data that made up the pictures, from objects to backgrounds, from lighting to shading, was dumped out of the system. First, Woody’s hat disappeared. Then his boots. Then he disappeared entirely. One by one, the other characters began to vanish, too: Buzz, Mr. Potato Head, Hamm, Rex. Whole sequences—poof!—were deleted from the drive. Oren

In the name of speed, Morse and Vail had realized that they could save strokes by reserving the shorter sequences of dots and dashes for the most common letters. But which letters would be used most often? Little was known about the alphabet’s statistics. In search of data on the letters’ relative frequencies, Vail was inspired to visit the local newspaper office in Morristown, New Jersey, and look over the type cases.

I like to ensure that I have music and art all around me. My personal favorite is old maps. What I love about old maps is that they are both beautiful and imperfect. These imperfections represent that some of the most talented in history were still very wrong (early cartography was very difficult). As the majority of my work is analysis and advisory, I find it a valuable reminder that my knowledge is limited. No matter how much data or insight I have, I can never fully “map out” any business. Yet, despite the incompleteness of these early cartographers, so much was learned of the world. So much done and accomplished. Therefore, these maps, or art pieces, serve as something to inspire both humility and achievement. This simple environmental factor helps my productivity and the overall quality of my work. Again, it’s like adding positive dice to my hand that are rolled each day.

High-quality and transparent data, clearly documented, timely rendered, and publicly available are the sine qua non of competent public health management. During a pandemic, reliable and comprehensive data are critical for determining the behavior of the pathogen, identifying vulnerable populations, rapidly measuring the effectiveness of interventions, mobilizing the medical community around cutting-edge disease management, and inspiring cooperation from the public. The shockingly low quality of virtually all relevant data pertinent to COVID-19, and the quackery, the obfuscation, the cherrypicking and blatant perversion would have scandalized, offended, and humiliated every prior generation of American public health officials. Too often, Dr. Fauci was at the center of these systemic deceptions. The “mistakes” were always in the same direction—inflating the risks of coronavirus and the safety and efficacy of vaccines in

As I came to understand, in retrospect, the magnetic quality that these works held for me, I came to understand that what motivated these men was not Earthly prizes or the respect of colleagues, but that they put their souls and minds on something and reached the extraordinary place where the mind could no longer produce data of the type that they wanted, and they were in the territory of inspiration, where their intuitions accelerated and they knew that there was something more than the realm of time and space and matter, something more than physical life.

Trump doesn’t happen in a country where things are going well. People give in to their baser instincts when they lose faith in the future. The pessimism and anger necessary for this situation has been building for a generation, and not all on one side. A significant number of Trump voters voted for Obama eight years ago. A lot of those were in rust-belt states that proved critical to his election. What happened there? Trump also polled 2–1 among veterans, despite his own horrific record of deferments and his insulting of every vet from John McCain to Humayun Khan. Was it possible that his rhetoric about ending “our current policy of regime change” resonated with recently returned vets? The data said yes. It may not have been decisive, but it likely was one of many factors. It was also common sense, because this was one of his main themes on the campaign trail—Trump clearly smelled those veteran votes. The Trump phenomenon was also about a political and media taboo: class. When the liberal arts grads who mostly populate the media think about class, we tend to think in terms of the heroic worker, or whatever Marx-inspired cliché they taught us in college. Because of this, most pundits scoff at class, because when they look at Trump crowds, they don’t see Norma Rae or Matewan. Instead, they see Married with Children, a bunch of tacky mall-goers who gobble up crap movies and, incidentally, hate the noble political press. Our take on Trump voters was closer to Orwell than Marx: “In reality very little was known about the proles. It was not necessary to know much.” Beyond the utility that calling everything racism had for both party establishments, it was good for that other sector, the news media.

G. Stanley Hall, a creature of his times, believed strongly that adolescence was determined – a fixed feature of human development that could be explained and accounted for in scientific fashion. To make his case, he relied on Haeckel's faulty recapitulation idea, Lombroso's faulty phrenology-inspired theories of crime, a plethora of anecdotes and one-sided interpretations of data. Given the issues, theories, standards and data-handling methods of his day, he did a superb job. But when you take away the shoddy theories, put the anecdotes in their place, and look for alternate explanations of the data, the bronze statue tumbles hard. I have no doubt that many of the street teens of Hall's time were suffering or insufferable, but it's a serious mistake to develop a timeless, universal theory of human nature around the peculiarities of the people of one's own time and place.

If Bezos took one leadership principle most to heart—which would also come to define the next half decade at Amazon—it was principal #8, “think big”: Thinking small is a self-fulfilling prophecy. Leaders create and communicate a bold direction that inspires results. They think differently and look around corners for ways to serve customers. In 2010, Amazon was a successful online retailer, a nascent cloud provider, and a pioneer in digital reading. But Bezos envisioned it as much more. His shareholder letter that year was a paean to the esoteric computer science disciplines of artificial intelligence and machine learning that Amazon was just beginning to explore. It opened by citing a list of impossibly obscure terms such as “naïve Bayesian estimators,” “gossip protocols,” and “data sharding.” Bezos wrote: “Invention is in our DNA and technology is the fundamental tool we wield to evolve and improve every aspect of the experience we provide our customers.

[THE DAILY BREATH] Blaise Pascal, the famous mathematician, once said: "To those who wish to see, God gives them sufficient light. To those who doesn't wish to see, God gives them sufficient darkness." Seeing the Truth is a choice. Listening to my words is a choice. Healing is a choice. If want scientific evidence about the existence of God, there is a wealth of data to support it. Dr. Jeffrey Long, M.D. used the best scientific techniques available today to study more than 4,000 people who had near-death experiences and found themselves face to face with our Heavenly Father. Read the book "God and the Afterlife" and you will find it. If you want scientific evidence about Jesus being the Son of God, Lee Strobel, an atheist investigative journalist discovered it. Read the book "The Case for Christ" and you will find it. If you want scientific evidence about Jesus still healing today, study the ministries of Dr. Charles Ndifon, T.L. Osborn, Kathryn Kuhlman among others, and you will find it. But most importantly, if you want to fill the emptiness within you, and experience the perfect love, mercy and forgiveness, if you want to live in the peace of our Heavenly Father, give your body, your mind and your heart to Christ. Give your life to Jesus. The empty place you feel in your heart is reserved only for the spirit of Christ and nothing from this world will fill it. Look up to heaven, behold Jesus and Live.

Your story isn’t powerful enough if all it does is lead the horse to water; it has to inspire the horse to drink, too. On social media, the only story that can achieve that goal is one told with native content. Native content amps up your story’s power. It is crafted to mimic everything that makes a platform attractive and valuable to a consumer—the aesthetics, the design, and the tone. It also offers the same value as the other content that people come to the platform to consume. Email marketing was a form of native content. It worked well during the 1990s because people were already on email; if you told your story natively and provided consumers with something they valued on that platform, you got their attention. And if you jabbed enough to put them in a purchasing mind-set, you converted. The rules are the same now that people spend their time on social media. It can’t tell you what story to tell, but it can inform you how your consumer wants to hear it, when he wants to hear it, and what will most make him want to buy from you. For example, supermarkets or fast-casual restaurants know from radio data that one of the ideal times to run an ad on the radio is around 5:00 P.M., when moms are picking up the kids and deciding what to make for dinner, and even whether they have the energy to cook. Social gives you the same kind of insight. Maybe the data tells you that you should post on Facebook early in the morning before people settle

The motor activities we take for granted—getting out of a chair and walking across a room, picking up a cup and drinking coffee,and so on—require integration of all the muscles and sensory organs working smoothly together to produce coordinated movements that we don't even have to think about. No one has ever explained how the simple code of impulses can do all that. Even more troublesome are the higher processes, such as sight—in which somehow we interpret a constantly changing scene made of innumerable bits of visual data—or the speech patterns, symbol recognition, and grammar of our languages.Heading the list of riddles is the "mind-brain problem" of consciousness, with its recognition, "I am real; I think; I am something special." Then there are abstract thought, memory, personality,creativity, and dreams. The story goes that Otto Loewi had wrestled with the problem of the synapse for a long time without result, when one night he had a dream in which the entire frog-heart experiment was revealed to him. When he awoke, he knew he'd had the dream, but he'd forgotten the details. The next night he had the same dream. This time he remembered the procedure, went to his lab in the morning, did the experiment, and solved the problem. The inspiration that seemed to banish neural electricity forever can't be explained by the theory it supported! How do you convert simple digital messages into these complex phenomena? Latter-day mechanists have simply postulated brain circuitry so intricate that we will probably never figure it out, but some scientists have said there must be other factors.

Well before the end of the 20th century however print had lost its former dominance. This resulted in, among other things, a different kind of person getting elected as leader. One who can present himself and his programs in a polished way, as Lee Quan Yu you observed in 2000, adding, “Satellite television has allowed me to follow the American presidential campaign. I am amazed at the way media professionals can give a candidate a new image and transform him, at least superficially, into a different personality. Winning an election becomes, in large measure, a contest in packaging and advertising. Just as the benefits of the printed era were inextricable from its costs, so it is with the visual age. With screens in every home entertainment is omnipresent and boredom a rarity. More substantively, injustice visualized is more visceral than injustice described. Television played a crucial role in the American Civil rights movement, yet the costs of television are substantial, privileging emotional display over self-command, changing the kinds of people and arguments that are taken seriously in public life. The shift from print to visual culture continues with the contemporary entrenchment of the Internet and social media, which bring with them four biases that make it more difficult for leaders to develop their capabilities than in the age of print. These are immediacy, intensity, polarity, and conformity. Although the Internet makes news and data more immediately accessible than ever, this surfeit of information has hardly made us individually more knowledgeable, let alone wiser, as the cost of accessing information becomes negligible, as with the Internet, the incentives to remember it seem to weaken. While forgetting anyone fact may not matter, the systematic failure to internalize information brings about a change in perception, and a weakening of analytical ability. Facts are rarely self-explanatory; their significance and interpretation depend on context and relevance. For information to be transmuted into something approaching wisdom it must be placed within a broader context of history and experience. As a general rule, images speak at a more emotional register of intensity than do words. Television and social media rely on images that inflamed the passions, threatening to overwhelm leadership with the combination of personal and mass emotion. Social media, in particular, have encouraged users to become image conscious spin doctors. All this engenders a more populist politics that celebrates utterances perceived to be authentic over the polished sound bites of the television era, not to mention the more analytical output of print. The architects of the Internet thought of their invention as an ingenious means of connecting the world. In reality, it has also yielded a new way to divide humanity into warring tribes. Polarity and conformity rely upon, and reinforce, each other. One is shunted into a group, and then the group polices once thinking. Small wonder that on many contemporary social media platforms, users are divided into followers and influencers. There are no leaders. What are the consequences for leadership? In our present circumstances, Lee's gloomy assessment of visual media's effects is relevant. From such a process, I doubt if a Churchill or Roosevelt or a de Gaulle can emerge. It is not that changes in communications technology have made inspired leadership and deep thinking about world order impossible, but that in an age dominated by television and the Internet, thoughtful leaders must struggle against the tide.

Isaac Asimov’s short story “The Fun They Had” describes a school of the future that uses advanced technology to revolutionize the educational experience, enhancing individualized learning and providing students with personalized instruction and robot teachers. Such science fiction has gone on to inspire very real innovation. In a 1984 Newsweek interview, Apple’s co-founder Steve Jobs predicted computers were going to be a bicycle for our minds, extending our capabilities, knowledge, and creativity, much the way a ten-speed amplifies our physical abilities. For decades, we have been fascinated by the idea that we can use computers to help educate people. What connects these science fiction narratives is that they all imagined computers might eventually emulate what we view as intelligence. Real-life researchers have been working for more than sixty years to make this AI vision a reality. In 1962, the checkers master Robert Nealey played the game against an IBM 7094 computer, and the computer beat him. A few years prior, in 1957, the psychologist Frank Rosenblatt created Perceptron, the first artificial neural network, a computer simulation of a collection of neurons and synapses trained to perform certain tasks. In the decades following such innovations in early AI, we had the computation power to tackle systems only as complex as the brain of an earthworm or insect. We also had limited techniques and data to train these networks. The technology has come a long way in the ensuing decades, driving some of the most common products and apps today, from the recommendation engines on movie streaming services to voice-controlled personal assistants such as Siri and Alexa. AI has gotten so good at mimicking human behavior that oftentimes we cannot distinguish between human and machine responses. Meanwhile, not only has the computation power developed enough to tackle systems approaching the complexity of the human brain, but there have been significant breakthroughs in structuring and training these neural networks.

We need to be humble enough to recognize that unforeseen things can and do happen that are nobody’s fault. A good example of this occurred during the making of Toy Story 2. Earlier, when I described the evolution of that movie, I explained that our decision to overhaul the film so late in the game led to a meltdown of our workforce. This meltdown was the big unexpected event, and our response to it became part of our mythology. But about ten months before the reboot was ordered, in the winter of 1998, we’d been hit with a series of three smaller, random events—the first of which would threaten the future of Pixar. To understand this first event, you need to know that we rely on Unix and Linux machines to store the thousands of computer files that comprise all the shots of any given film. And on those machines, there is a command—/bin/rm -r -f *—that removes everything on the file system as fast as it can. Hearing that, you can probably anticipate what’s coming: Somehow, by accident, someone used this command on the drives where the Toy Story 2 files were kept. Not just some of the files, either. All of the data that made up the pictures, from objects to backgrounds, from lighting to shading, was dumped out of the system. First, Woody’s hat disappeared. Then his boots. Then he disappeared entirely. One by one, the other characters began to vanish, too: Buzz, Mr. Potato Head, Hamm, Rex. Whole sequences—poof!—were deleted from the drive. Oren Jacobs, one of the lead technical directors on the movie, remembers watching this occur in real time. At first, he couldn’t believe what he was seeing. Then, he was frantically dialing the phone to reach systems. “Pull out the plug on the Toy Story 2 master machine!” he screamed. When the guy on the other end asked, sensibly, why, Oren screamed louder: “Please, God, just pull it out as fast as you can!” The systems guy moved quickly, but still, two years of work—90 percent of the film—had been erased in a matter of seconds. An hour later, Oren and his boss, Galyn Susman, were in my office, trying to figure out what we would do next. “Don’t worry,” we all reassured each other. “We’ll restore the data from the backup system tonight. We’ll only lose half a day of work.” But then came random event number two: The backup system, we discovered, hadn’t been working correctly. The mechanism we had in place specifically to help us recover from data failures had itself failed. Toy Story 2 was gone and, at this point, the urge to panic was quite real. To reassemble the film would have taken thirty people a solid year. I remember the meeting when, as this devastating reality began to sink in, the company’s leaders gathered in a conference room to discuss our options—of which there seemed to be none. Then, about an hour into our discussion, Galyn Susman, the movie’s supervising technical director, remembered something: “Wait,” she said. “I might have a backup on my home computer.” About six months before, Galyn had had her second baby, which required that she spend more of her time working from home. To make that process more convenient, she’d set up a system that copied the entire film database to her home computer, automatically, once a week. This—our third random event—would be our salvation. Within a minute of her epiphany, Galyn and Oren were in her Volvo, speeding to her home in San Anselmo. They got her computer, wrapped it in blankets, and placed it carefully in the backseat. Then they drove in the slow lane all the way back to the office, where the machine was, as Oren describes it, “carried into Pixar like an Egyptian pharaoh.” Thanks to Galyn’s files, Woody was back—along with the rest of the movie.