Data Limitations Quotes

Errors using inadequate data are much like those using no data at all.

Modern statisticians are familiar with the notion that any finite body of data contains only a limited amount of information on any point under examination; that this limit is set by the nature of the data themselves, and cannot be increased by any amount of ingenuity expended in their statistical examination: that the statistician's task, in fact, is limited to the extraction of the whole of the available information on any particular issue.

The problem with data is that it says a lot, but it also says nothing. 'Big data' is terrific, but it's usually thin. To understand why something is happening, we have to engage in both forensics and guess work.

We know: of course, with regard to the market and similar social structures, a great many facts which we cannot measure and on which indeed we have only some very imprecise and general information.

Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.

We need to be able to make decisions even though part of the information that we have is incorrect and wrong.

No amount of data will tell you if a feature should be in the product, because it doesn't exist. You need to have a very clear leader with a clear point of view... otherwise, you get a mishmash of features and stuff that doesn't make a lot of sense.

Knowledge is invariably a matter of degree: you cannot put your finger upon even the simplest datum and say this we know.

Big data sets are never complete.

Knowledge about limitations of your data collection process affects what inferences you can draw from the data.

I don't know whether I'm, like, jumping the gun but it's possible that in the future we may be able to use the information that we can't receive at the moment.

Big data will never give you big ideas... Big data doesn't facilitate big leaps of the imagination. It will never conjure up a PC revolution or any kind of paradigm shift. And while it might tell you what to aim for, it can't tell you how to get there

Data don't generate theory - only researchers do that.

The type of measure used placed constraints on which statistics can be used.

If we start to use social media data sets to take the pulse of a nation or understand a crisis - or actually use it to deploy resources - we are getting a skewed picture of what is happening.

A lot of things can't be modeled very well.

No matter how invasive the technologies at their disposal, marketers and pollsters never come to terms with the living process through which people choose products or candidates; they are looking at what people just bought or thought, and making calculations based on that after-the-fact data.

Unlike the position that exists in the physical sciences, in economics and other disciplines that deal with essentially complex phenomena, the aspects of the events to be accounted for about which we can get quantitative data are necessarily limited and may not include the important ones.

Data adds concrete information to a teacher's observations and intuition, but it will never replace experience, personal relationships, and cultural understanding.

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.

I've seen how the issues that come across a president's desk are always the hard ones - the problems where no amount of data or numbers will get you to the right answer.

Macroeconomics, even with all of our computers and with all of our information - is not an exact science and is incapable of being an exact science.

I wish I could calculate my way to a bigger audience, but I don't think I'm smart enough. Actually, I don't think anyone is smart enough. Most calculations along those lines fail.

A computer can tell you down to the dime what you've sold, but it can never tell you how much you could have sold.