A Quote by Todd Park

Data by itself is not useful. Data is only useful if it can be applied for public benefit. — © Todd Park
Data by itself is not useful. Data is only useful if it can be applied for public benefit.
Machine learning and artificial intelligence applications are proving to be especially useful in the ocean, where there is both so much data - big surfaces, deep depths - and not enough data - it is too expensive and not necessarily useful to collect samples of any kind from all over.
Rob Engle and I are concerned with extracting useful implications from economic data, and so the properties of the data are of particular importance.
Rule 1. Original data should be presented in a way that will preserve the evidence in the original data for all the predictions assumed to be useful.
The data are what matter in economics, and the more ruthlessness that an economist can summon to make sense of the data, the more useful his findings will be.
Data isn't information. ... Information, unlike data, is useful. While there's a gulf between data and information, there's a wide ocean between information and knowledge. What turns the gears in our brains isn't information, but ideas, inventions, and inspiration. Knowledge-not information-implies understanding. And beyond knowledge lies what we should be seeking: wisdom.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
Data is not useful until it becomes information.
Oppression tries to defend itself by its utility. But we have seen that it is one of the lies of the serious mind to attempt to give the word "useful" an absolute meaning; nothing is useful if it is not useful to man; nothing is useful to man if the latter is not in a position to define his own ends and values, if he is not free.
Often, people think that individual data is the most valuable thing they can collect. But it's not useful to know what I am doing or where I am, unless you're particularly interested in me, which is weird. But it is very useful to know what a population of people are doing.
When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern has been privacy - the disclosure of sensitive data about individuals, either directly to the public or indirectly from anonymised data sets through computational processes of re-identification.
To create an open protocol which helps coordinate resources towards a common goal, the resources need to be known at some level in the same way a lot of of data on the web needs to be public for it to be traversable and useful.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
Shape clay into a vessel; It is the space within that makes it useful. Cut doors and windows for a room; It is the holes which make it useful. Therefore benefit comes from what is there; Usefulness from what is not there.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
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