What is the difference between Data and Information

Difference between Data and Information

In this article, we will understand the meaning of information, data, key differences between data and information, and their uses.

Data and Information are often mistaken to be the same and used in place of each other. But this is not true, as they are independent of each other.

However, the fact is that they seem to be interlinked by a bond known as processing, ie. Data – Processing – Information.

To get a fair understanding of the difference, we will have to first get an insight into each term individually.

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What is Data?

Data is known to have been derived from the Latin word – datum, which stands for something given.

The history of its existence dates back to 1640 when it was used for the first time in English.

It also has a dictionary and philosophical meaning, but in general, Data is some kind of facts, numbers, or pieces of write up which may or may not have a complete meaningful understanding to humans because of it being in unorganized and scattered form.

These unorganized data will have to be interpreted, arranged, and processed either manually or using technology like computers and presented in a form to be able to understand and for extracting meaningful output. 

A data is either standalone or combination of characters (#, *, &, /) alphabets (A to Z or a to z), numbers (0 to 9), and collectively referred to as raw things.

These entities do not have a context and can often be misleading to anyone reading or interpreting it.

The interpretation of a picture without any text or a video without any sound might vary between individuals because they do not carry any definite meaning or understanding.

For example, 26th Jan, 15th Aug, 1st May, 2nd Oct gives no clarity except some list of dates because it is incomplete or not organized.

It could be either someone’s birthday, anniversary, or a deadline for some assignments.

Now, if we organize it in a proper order giving it a title – List of government holidays in India, will make it more sensible and impart a common understanding for everyone reading it. 

Historic data is used by historians for their research programs and also to understand the practices and cultures followed by early humans.

The temperature readings collected in a day are nothing but a form of data, and the output is when it is processed and analyzed to find out the minimum and maximum temperature of that particular day.

Data collection in any business has no relevance in its raw form, but when filtered, structured, and analyzed will help in building the organization’s growth strategies.

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How is data categorized?

The data is primarily categorized into two types, as below:-

Qualitative data

This type of data describes characteristics and is not easily measurable. Qualitative data is often recorded based on the observations.

It is referred to as categorical data in statistical analysis, as the data collected is based on some categories or attributes.

For example, customer feedback on service quality will be either from it being Very good, Good, Neutral, Bad, or Very bad.

It can be further subcategorized as Nominal data that do not have a specified and distinct sequence or order, whereas ordinal data does have a sequential ordering.

Gender, race are examples of nominal data, and Performance, Service feedback is examples of ordinal data.

Ordinal data can be sometimes numeric but do not have numeric properties.

The qualitative data can be collected online forums, interviews, survey chat, and group discussions. 

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Quantitative data

This type of data is countable, measurable, and often articulated in numbers.

With this data, we can get answers to the questions involving quantity, value, size, etc.

The quantitative data has to be validated before using it as it impacts accuracy during the research or analysis.

Some of the examples of quantitative data are the Amount of money in the wallet, Number of students in a class, Height of a building, etc.

It can be further subcategorized into Discrete data which has finite numbers and cannot be divided any further, the continuous data is continuous, and can have any number (whole or fractions) within a specified range.

Examples of discrete data are the number of people in an office, the number of students appearing for the examination, the number of votes in an election.

Examples of discrete data are the height of student, wind speed, race time. Quantitative data are highly reliable but has limited outcomes.

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What is Information?

Information is known to have derived from the Latin word-informare, which means an act to inform.

The history of its existence dates back to the 14th century when it was used for the first time.

It also has a dictionary and philosophical meaning, but in general, Information is simply a result of processed data.

In computers, it is an output obtained from the processing of raw input data by a particular program or software.

The information is relevant and understood by humans. It is a knowledge that facilitates making a business and personal decision or judgment.

For example, report cards, presentations, receipts, etc. 

Information will be in an organized, structured form and without any unwanted details to give logical meaning to the analysts or researchers.

The modern world is very complex, and one needs to be competitive for its survival.

It obliges the people to keep an update of all the happenings in their surroundings.

How is Information basically used?

Information is mainly used for Planning, Recording, Analysis, and controlling.


Information plays a vital role in the planning stage and aids in decision making.

An organization must be aware of its resources, stakeholders, infrastructures to remain ahead of its competitors.

The information from the data analysis of market research can help organizations to develop their strategies or offerings.


It is always a good practice to record all the required information. Like academics track and records the admissions and number of students passing every year to enable them to make decisions, a business organization must track the useful information such as expenses, sales, and purchases to help in future strategies.


The information is further used to analyze the percentage of sales, costs incurred and the profits margins, etc. and help in cost optimization.


It becomes easier for an organization to keep control of its processes after having all the required information and analysis in place.

It can also help in identifying the trend of your company. The cost, time, and resources can be managed effectively in achieving the results.

What are the major differences between data and information?

Let us understand the key differences between data and Information with some examples.

  Parameter  Data  Information  
  FormIt is a raw fact about any event, conditions, entity, etc. collected for further processing. It is in scattered form and has no relevance.It is a processed fact which is structured, organized, and filtered from unwanted details to create meaningful knowledge or information.  
SignificanceAs it is raw and standalone, it has no meaning.As it is processed data, it has relevant significance and helps in taking action.  
RepresentationIt is in the tabular formats, graphical illustrations, and in a hierarchical tree structure.It is in the form of language, thoughts, and ideasbased on the data.  
DependencyData is independent and standalone as it consists of numerous details in a random structure or manner.  The information is dependent on data. You cannot get information if there is no data.
ReliabilityThe data in its raw form can be interpreted in many ways since it is without any specific perspective. A ten-digit number can be interpreted as a phone number or a serial number of any software program.  The processed data or information is highly reliable as it gives some logical understanding and has a specific perspective.
Input / OutputData is an input and is processed to result in information.Information is output once the data is processed.  
AnalysisYou cannot analyze data in its raw form.You can analyze the information as it is processed data.  
Decision makingCollection of data has no meaning and hence does not help in decision makingAs the information is well organized, structured, and filtered details, it helps in decision making.  
UsefulnessData is useful since it creates a foundation for information.From a business perspective, data does not carry any significant value, but the information becomes very helpful and handy.  
Examplea. Data about the scores of the students in a class along with their names and roll numbers b. Data about the phone numbers and addresses of people in a particular statea. Report cards of the students.     b. Directory

What is DIKW (Data Information Knowledge Wisdom)?

DIKW is the model used to discuss data, information, knowledge, wisdom, and its connections.

It is structural or functional connections between data, information, information, and knowledge.

Information is data, but data is not inherently information.

Wisdom also consists of knowledge, which in turn is data, but knowledge, for instance, is not necessarily wisdom.

Wisdom, therefore, is a subset of knowledge, a subset of facts, a subset of data.

Data is an unorganized piece of information, and when it is put together in a structured and organized manner is known as information.

In technical vocabulary, data is called input, and the result generated from the processed data is called as an output.

Data can be any set of numbers, characters, and alphabets, and do not carry any relevance in its raw form until it is analyzed and transformed into useful and meaningful information.

Every business organizations gather data and process it into valuable information to help in shaping up their policies and growth strategy.

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