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Data, Information, and Intelligence

What the terms mean, how they relate to each other, and why they are not mutually exclusive


Facts are statements that are true;

Data are facts that have been recorded;

Information is data that have been given for context or has been used to answer a question; and

Intelligence is information relevant to decision making.


The difference between data, information and intelligence can be a source of confusion for some. It doesn't help matters that it's possible for something to be all three things at once.

In this chapter, we will clarify exactly what each term means, how they all relate to each other, and why the terms are not mutually exclusive.


Data are facts that have been recorded.

Note: A singular fact that has been recorded is referred to as a datum.

Often data is recorded into something like a log, a spreadsheet, or a table as below.

A table showing the height of the world’s five tallest mountains

A record of data may be referred to as a dataset.

In this case, we have a dataset on the height and locations of the world's tallest five mountains. If these facts had never been written down, they would still be facts. The mountains would still be the same height and in the same location. However, because they have been written down, these facts have become data.

It is possible to recall data on anything from the weather to speed to populations. Here we have a dataset on the defensive statistics of five English football as from the 2020/21 Premier League season.

A table showing the number of tackles, interceptions, and clearances by five English footballers in the 2020/21 Premier League season

By interrogating this data and using it to answer questions we can discover information about the players’ performance.


Information is data that has been given meaning or context or that has been used to answer a question.

By interrogating our dataset, we can answer questions and therefore provide information.

For example, if we were asked how many tackles Eric Dier made, we could interrogate the dataset to discover that Eric Dyer made 311 tackles.

If we were asked which defender made the most clearances, we could interrogate the data set to discover that Harry Maguire made the most clearances.

If we were asked if Mings made more tackles than Stones, we could interrogate the dataset to discover that Mings did not make more tackles and John Stones.

You get the idea. So how does this relate to intelligence?


As we already know, intelligence is information relevant to decision making.

So, if the England football manager was wanting to pick two defenders for the England football team, he could consult this dataset to see which players had the best defensive statistics and then use this information to inform his decision about who to pick. This information would also act as intelligence in this case, as it is relevant to his decision.

The same table as above, but with the players who have the best defensive statistics highlighted in green

However, if the England rugby manager was deciding to pick who to play for the England rugby team, this dataset would not act as intelligence, as the information it contains would have no relevance to his decision.

Visualising the Relationship between Data, Information, and Intelligence

There are two easy ways to visualise the relationship between facts, data, information and intelligence: The Pyramid and The Funnel.

The Pyramid.

For the pyramid, imagine a pyramid with facts acting as the bottom layer of bricks;

When these facts are recorded, they become data, which is the next layer up;

When this data is given context on meaning, or is used to answer a question, it becomes information (the penultimate layer); and finally

When information is relevant to decision making, it also becomes intelligence, the apex of the pyramid.

The Funnel

The other method is known as the funnel, and it works in pretty much the same way as a pyramid, but in reverse.

You start off with a pool of facts at the top;

These are then funnelled down to become data when recorded;

This data is then further funnelled down to become information when it is given context or used to answer a question; and finally

That information is funnelled down again into intelligence if it is relevant to decision making.

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