2 min readOct 10, 2020


Data: 10 Quotes

“Before anything can be reasoned upon to a conclusion, certain facts, principles, or data, to reason from, must be established, admitted, or denied.” (Thomas Paine, “Rights of Man”, 1791)

“The errors which arise from the absence of facts are far more numerous and more durable than those which result from unsound reasoning respecting true data.” (Charles Babbage, “On the Economy of Machinery and Manufactures”, 1832)

“It is a capital mistake to theorise before one has data.” (Arthur C Doyle, “The Adventures of Sherlock Holmes”, 1892)

“Not even the most subtle and skilled analysis can overcome completely the unreliability of basic data.” (Roy D G Allen, “Statistics for Economists”, 1951)

“Data in isolation are meaningless, a collection of numbers. Only in context of a theory do they assume significance […]” (George Greenstein, “Frozen Star”, 1983)

“Information is data that has been given meaning by way of relational connection. This ‘meaning’ can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it.” (Russell L Ackoff, “Towards a Systems Theory of Organization”, 1985)

“Intuition becomes increasingly valuable in the new information society precisely because there is so much data.” (John Naisbitt, “Re-Inventing the Corporation”, 1988)

“Data are collected as a basis for action. Yet before anyone can use data as a basis for action the data have to be interpreted. The proper interpretation of data will require that the data be presented in context, and that the analysis technique used will filter out the noise.” (Donald J Wheeler, “Understanding Variation: The Key to Managing Chaos” 2nd Ed., 2000)

“[…] you simply cannot make sense of any number without a contextual basis. Yet the traditional attempts to provide this contextual basis are often flawed in their execution. […] Data have no meaning apart from their context. Data presented without a context are effectively rendered meaningless.” (Donald J Wheeler, “Understanding Variation: The Key to Managing Chaos” 2nd Ed., 2000)

“To find signals in data, we must learn to reduce the noise — not just the noise that resides in the data, but also the noise that resides in us. It is nearly impossible for noisy minds to perceive anything but noise in data. […] Signals always point to something. In this sense, a signal is not a thing but a relationship. Data becomes useful knowledge of something that matters when it builds a bridge between a question and an answer. This connection is the signal.” (Stephen Few, “Signal: Understanding What Matters in a World of Noise”, 2015)

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