Big Data Quotes

The only way to stop big data from becoming big brother is introduce privacy laws that protect the basic human rights online.

Big data is based on the feedback economy where the Internet of Things places sensors on more and more equipment. More and more data is being generated as medical records are digitized, more stores have loyalty cards to track consumer purchases, and people are wearing health-tracking devices. Generally, big data is more about looking at behavior, rather than monitoring transactions, which is the domain of traditional relational databases. As the cost of storage is dropping, companies track more and more data to look for patterns and build predictive models".

Jack's marketing books had been a part of her life for so long that she had ceased to register their presence, simply moving them from the couch to the coffee table, from the bed to the nightstand. How to Sell Everything to Anybody. Eight Great Habits of CEOs. They all seemed to involve numbers, as if you could simply count yourself to riches, like following sheep to sleep.

Erica Bauermeister

Pull approaches differ significantly from push approaches in terms of how they organize and manage resources. Push approaches are typified by "programs" - tightly scripted specifications of activities designed to be invoked by known parties in pre-determined contexts. Of course, we don't mean that all push approaches are software programs - we are using this as a broader metaphor to describe one way of organizing activities and resources. Think of thick process manuals in most enterprises or standardized curricula in most primary and secondary educational institutions, not to mention the programming of network television, and you will see that institutions heavily rely on programs of many types to deliver resources in pre-determined contexts.Pull approaches, in contrast, tend to be implemented on "platforms" designed to flexibly accommodate diverse providers and consumers of resources. These platforms are much more open-ended and designed to evolve based on the learning and changing needs of the participants. Once again, we do not mean to use platforms in the literal sense of a tangible foundation, but in a broader, metaphorical sense to describe frameworks for orchestrating a set of resources that can be configured quickly and easily to serve a broad range of needs. Think of Expedia's travel service or the emergency ward of a hospital and you will see the contrast with the hard-wired push programs.

From a mathematical point of view, however, trust is hard to quantify. That's a challenge for people building models. Sadly, it's far easier to keep counting arrests, to build models that assume we're birds of a feather and treat us as such. Innocent people surrounded by criminals get treated badly, and criminals surrounded by law-abiding public get a pass. And because of the strong correlation between poverty and reported crime, the poor continue to get caught up in the digital dragnets. The rest of us barely have to think about them.

At the federal level, this problem could be greatly alleviated by abolishing the Electoral College system. It's the winner-take-all mathematics from state to state that delivers so much power to a relative handful of voters. It's as if in politics, as in economics, we have a privileged 1 percent. And the money from the financial 1 percent underwrites the microtargeting to secure the votes of the political 1 percent. Without the Electoral College, by contrast, every vote would be worth exactly the same. That would be a step toward democracy.

Will those insights be tested,or simply used to justify the status quo and reinforce prejudices? When I consider the sloppy and self-serving ways that companies use data, I'm often reminded of phrenology, a pseudoscience that was briefly the rage in the nineteenth century. Phrenologists would run their fingers over the patient's skull, probing for bumps and indentations. Each one, they thought, was linked to personality traits that existed in twenty-seven regions of the brain. Usually the conclusion of the phrenologist jibed with the observations he made. If the patient was morbidly anxious or suffering from alcoholism, the skull probe would usually find bumps and dips that correlated with that observation - which, in turn, bolstered faith in the science of phrenology. Phrenology was a model that relied on pseudoscientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. Models like the ones that red-lighted Kyle Behm and black-balled foreign medical students and St. George's can lock people out, even when the "science" inside them is little more than a bundle of untested assumptions.

Will those insights be tested, or simply used to justify the status quo and reinforce prejudices? When I consider the sloppy and self-serving ways that companies use data, I'm often reminded of phrenology, a pseudoscience that was briefly the rage in the nineteenth century. Phrenologists would run their fingers over the patient's skull, probing for bumps and indentations. Each one, they thought, was linked to personality traits that existed in twenty-seven regions of the brain. Usually the conclusion of the phrenologist jibed with the observations he made. If the patient was morbidly anxious or suffering from alcoholism, the skull probe would usually find bumps and dips that correlated with that observation - which, in turn, bolstered faith in the science of phrenology. Phrenology was a model that relied on pseudoscientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. Models like the ones that red-lighted Kyle Behm and black-balled foreign medical students and St. George's can lock people out, even when the "science" inside them is little more than a bundle of untested assumptions.

Will those insights be tested,or simply used to justify the status quo and reinforce prejudices? When I consider the sloppy and self-serving ways that companies use data, I'm often reminded of phrenology, a pseudoscience that was briefly the rage in the nineteenth century. Phrenologists would run their fingers over the patient's skull, probing for bumps and indentations. Each one, they thought, was linked to personality traits that existed in twenty-seven regions of the brain. Usually the conclusion of the phrenologist jibed with the observations he made. If the patient was morbidly anxious or suffering from alcoholism, the skull probe would usually find bumps and dips that correlated with that observation - which, in turn, bolstered faith in the science of phrenology. Phrenology was a model that relied on pseudoscientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. Models like the ones that red-lighted Kyle Behm and black-balled foreign medical students and St. George's can lock people out, even when the "science" inside them is little more than a bundle of untested assumptions.

Will those insights be tested, or simply used to justify the status quo and reinforce prejudices? When I consider the sloppy and self-serving ways that companies use data, I'm often reminded of phrenology, a pseudoscience that was briefly the rage in the nineteenth century. Phrenologists would run their fingers over the patient's skull, probing for bumps and indentations. Each one, they thought, was linked to personality traits that existed in twenty-seven regions of the brain. Usually the conclusion of the phrenologist jibed with the observations he made. If the patient was morbidly anxious or suffering from alcoholism, the skull probe would usually find bumps and dips that correlated with that observation - which, in turn, bolstered faith in the science of phrenology. Phrenology was a model that relied on pseudoscientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. Models like the ones that red-lighted Kyle Behm and black-balled foreign medical students and St. George's can lock people out, even when the "science" inside them is little more than a bundle of untested assumptions.