Big Data Quotes

“A reminder that Goodreads is owned by Amazon, and everything you do here supports Big Data and corporate surveillance. You should be concerned, especially if you read books about liberation.

A friend recommended StoryGraph, a Black-owned independent alternative.

Download your data and GTFO.”
― Anonymous

“Big data does not predict anything beyond the assumption of an idealized situation in a stable system.”
― Roger Spitz, Disrupt With Impact: Achieve Business Success in an Unpredictable World

“If you can't understand a study, the problem is with the study, not with you.”
― Seth Stephens-Davidowitz, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are

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

“Cloud is the digital wonderland of Internet of Things, powered by Artificial Intelligence and Big Data”
― Enamul Haque, Digital Transformation Through Cloud Computing: Developing a sustainable business strategy to eschew extinction

“As one Google Translate engineer put it, "when you go from 10,000 training examples to 10 billion training examples, it all starts to work. Data trumps everything.”
― Garry Kasparov, Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins

“Os políticos são um pouco como músicos, e o instrumento que eles tocam é o sistema emocional e bioquímico humano. Eles fazem um discurso e uma onda de medo varre o país. Publicam um tweet e há uma explosão de ódio. Não creio que devamos dar a estes músicos um instrumento mais sofisticado no qual tocar. Uma vez conseguindo manipular diretamente as nossas alavancas emocionais, gerando ansiedade, ódio, satisfação e tédio à sua vontade, a política vai tornar-se um mero circo emocional.Por muito que devamos recear o poder das grandes empresas, a História sugere que não estamos mais seguros nas mãos de governos todo- poderosos. Em janeiro de 2018, prefiro que as minhas informações estejam nas mãos de Mark Zuckerberg do que nas mãos de Vladimir Putin(...)”
― Yuval Noah Harari, 21 Lessons for the 21st Century

“For getting success in business with Data Science, predictions must be backed by timely strategic actions.”
― Shitalkumar R Sukhdeve, Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data : Illustrations with R & Python

“To which I might add that questions about the psychic, political and social effects of information are as applicable to the computer as to television. Although I believe the computer to be a vastly overrated technology, I mention it here because, clearly, Americans have accorded it their customary mindless inattention; which means they will use it as they are told, without a whimper. Thus, a central thesis of computer technology—that the principal difficulty we have in solving problems stems from insufficient data—will go unexamined. Until, years from now, when it will be noticed that the massive collection and speed-of-light retrieval of data have been of great value to large-scale organizations but have solved very little of importance to most people and have created at least as many problems for them as they may have solved.”
― Neil Postman, Amusing Ourselves to Death: Public Discourse in the Age of Show Business

“Search engine query data is not the product of a designed statistical experiment and finding a way to meaningfully analyse such data and extract useful knowledge is a new and challenging field that would benefit from collaboration. For the 2012–13 flu season, Google made significant changes to its algorithms and started to use a relatively new mathematical technique called Elasticnet, which provides a rigorous means of selecting and reducing the number of predictors required. In 2011, Google launched a similar program for tracking Dengue fever, but they are no longer publishing predictions and, in 2015, Google Flu Trends was withdrawn. They are, however, now sharing their data with academic researchers...

Google Flu Trends, one of the earlier attempts at using big data for epidemic prediction, provided useful insights to researchers who came after them...

The Delphi Research Group at Carnegie Mellon University won the CDC’s challenge to ‘Predict the Flu’ in both 2014–15 and 2015–16 for the most accurate forecasters. The group successfully used data from Google, Twitter, and Wikipedia for monitoring flu outbreaks.”
― Dawn E. Holmes, Big Data: A Very Short Introduction

“An integrated automation factory should ensure cost savings, stabilisation and reduced turnaround times across all services.”
― Enamul Haque, The Ultimate Modern Guide to Digital Transformation: The "Evolve or Die" thing clarified in a simpler way

“In the competitive world of digital marketing, converting prospects into loyal customers is the ultimate goal for any business. CallTrack.AI emerges as a revolutionary tool in this quest, leveraging the power of artificial intelligence to transform the lead generation process. How CallTrack.AI redefines the approach to capturing and nurturing leads, ultimately leading to higher conversion rates and a robust customer base?”
― David Smithers

“The Future of Lead Generation
CallTrack.AI stands at the forefront of a new era in lead generation. By harnessing the capabilities of AI, businesses can not only improve their lead generation processes but also revolutionize the way they interact with prospects. The result is a more efficient, personalized, and successful approach to converting leads into loyal customers. As AI continues to evolve, CallTrack.AI remains a pivotal tool for businesses looking to thrive in the digital marketplace.
Read more at CallTrack.Ai”
― David Smithers

“At the heart of the decoding problem is how to understand the vast information contained in neural signals, the challenge of what is being called "big data". For neuroscientists, big data is a means for exploring populations of neurons to discover the macroscopic signatures of dynamical systems, rather than attempting to make sense of the activity of individual neurons. Two surprising results from numerous experiments recording from neurons in different brain regions have revealed a wonderful secret of nature about the relation between the number of neurons recorded and and their dimensionality (the number of principal components required to explain a fixed percentage of variance). First, the dimensionality of the neural data is much smaller than the number of recorded neurons. Second, when dimensionality procedures are used to extract neuronal state dynamics, the resulting low-dimensional neural trajectories reveal portraits of the behavior of a dynamical system. This means that it may not be necessary to record from many more neurons within a brain region in order to accurately recover its internal state-space dynamics.”
― Eugene C. Goldfield, Bioinspired Devices: Emulating Nature’s Assembly and Repair Process

“We have to learn to interrogate our data collection process, not just our algorithms.”
― Cathy O'Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

“In the era where artificial intelligence and algorithms make more decisions in our lives and in organizations, the time has come for people to tap into their intuition as an adjunct to today’s technical capabilities. Our inner wisdom can embed empirical data with humanity.”
― Abhishek Ratna, small wins BIG SUCCESS: A handbook for exemplary success in post Covid19 Outbreak Era

“Two hundred million people signed on to a microblogging platform that helped them feel close to celebrities and other strangers they’d loathe in real life. Artificial intelligence and virtual reality were coming into vogue, again. Self-driving cars were considered inevitable. Everything was moving to mobile. Everything was up in the cloud. The cloud was an unmarked data center in the middle of Texas or Cork or Bavaria, but nobody cared. Everyone trusted it anyway.”
― Anna Wiener, Uncanny Valley

“Nevertheless, many of these models encoded human prejudice, misunderstanding, and bias into the software systems that increasingly managed our lives.”
― Cathy O'Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

“The question, however, is whether we've eliminated human bias or simply camouflaged it with technology.”
― Cathy O'Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

“Think of small data as a pond and big data as a whirlpool in an ocean.”
― Rupa Mahanti, Data Humour

“Más que la tierra o el dinero, más que la cuna. Información. Eso es lo que importa.”
― William Gibson, The Difference Engine

“We're still in the honeymoon phase of connectivity. Governments and corporations are punch-drunk on our data, and the rush to connect everything is driven by an even greater desire for power and market share.”
― Bruce Schneier, Click Here to Kill Everybody: Security and Survival in a Hyper-connected World

“[...] [A] world increasingly reliant on and in thrall to data. Big Data. Which in turn is panned for Big Truths by Big Algorithms, using Big Computers. But when your big data is corrupted by big silences, the truths you get are half-truths, at best. And often, for women, they aren't true at all.”
― Caroline Criado Pérez, Invisible Women: Data Bias in a World Designed for Men

“What Is Big Data and Cloud Computing?

According to Dr.P.S.Jagadeesh Kumar (Dr.PSJ Kumar);

"The Science Of Learning And Applying Complex Data By Exchanging Methods And Algorithms Between Human And Machine Is Known As Big Data (BD)"

"The Exchange Of Services Between Human And Internet To Pay And Apply Tools, Storages, And Applications Is Known As Cloud Computing (CC)”
― P.S. Jagadeesh Kumar

“I define that the tech industry switches in all directions contrary to what people believe as the norm for the new Metaverse. Why spend trillions of dollars on big data when it is becoming more useless? We need dynamic content to create a boom in the tech industry for the next millennium. Why hire someone with a 4 year college degree for a career in database administration when companies can't afford to pay 100k a year? We can manage information stores perfectly fine with google sheets or microsoft excel. I thought that utilizing AI would completely switch off problematics in relationship to Data As A Service when programs are dynamically building hash tables for objects in random access memory, storing them as blockchains Inna virtualized file container ;)." - Jonathan Roy Mckinney”
― Jonathan Roy Mckinney Gero EagleO2

“Moving computations to data allows us to design big data processing that otherwise would be very slow or not even feasible.”
― Tomasz Lelek, Software Mistakes and Tradeoffs: How to make good programming decisions

“Science, once a triumph of human intelligence, now seems headed into a morass of rhetoric about the power of big data and new computational methods, where the scientists' role is now as a technician, essentially testing existing theories on IBM Blue Gene supercomputers.
   But computers don't have insights. People do. And collaborative efforts are only effective when individuals are valued. Someone has to have an idea. Turing at Bletchley knew—or learned—this, but the lessons have been lost in the decades since. Technology, or rather AI technology, is now pulling "us" into "it." Stupefyingly, we now disparage Einstein to make room for talking-up machinery.”
― Erik J. Larson, The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do

“应用现代科学技术，加速实现平权。”
― BOJU WANG

“Privacy is now the evidence, not the obstacle.
Today, proof no longer requires exposure.
Privacy has always been here, it's just that it became more impossible to ignore now. As regulation tightens and data tracking gets worse, people are realizing privacy isn’t optional.”
― Olawale Daniel

“AI must be built by everyone, or eventually its benefits will belong to no one.”
― F.C. Quiles