Code360 powered by Coding Ninjas X Naukri.com. Code360 powered by Coding Ninjas X Naukri.com
Table of contents
1.
Introduction
2.
What is Data?
2.1.
Structured data
2.2.
Unstructured data 
2.3.
Semistructured data
3.
Characteristics of Data
4.
What is Information?
5.
Characteristics of Information
6.
Comparison Table Between Data and Information
7.
The Key Differences Between Data vs Information
8.
Example of Data and Information
9.
Frequently Asked Questions 
9.1.
What are 3 differences between data and information?
9.2.
What are the 5 examples of information?
9.3.
Which are the 3 main types of data?
10.
Conclusion 
Last Updated: Mar 27, 2024
Medium

Difference Between Data and Information

Author Lali Sharma
1 upvote
Crack Google SDE interview : Essential projects
Speaker
Saurav Prateek
SDE-2 @
20 Jun, 2024 @ 01:30 PM

Introduction

Hey! Do you often get confused between the data and the information? Do they have the same meaning? If you want to know about it, this article is for you. So let's dive right into it.

Difference between data & information

Recommended Topic, 8085 Microprocessor Pin Diagram

What is Data?

Data is the combination of raw facts and figures. It can be structured or unstructured. It does not follow a particular format. We perform processing on data to analyze or look into its insights. Data produced digitally combines numerical, textual, images, graphics, animations, gifs, audio, videos, etc., helpful for analysis, research, and decision-making. 

Data is vital in any organization as it is used for decision-making and evidence-based decisions.

Data is divided into three categories:

types of data

Structured data

As the name suggests, data is stored in a predefined format or structure. Specific rules are to be followed for storing and arranging data. Data is ordered, and thus data retrieval is more accessible. Structuring data makes it less complex, which makes its analysis more accessible. 

Example:

  1. Excel files 
  2. Relational Databases 
  3. Contact lists 
  4. Customer Relationship Management(CRM)
  5. Invoicing Systems 

Unstructured data 

Data that does not follow any predefined format for storage is called unstructured data. It does not follow any data model or schema. It cannot be stored in a traditional database. Maintaining unstructured data is complex.

Example:  

  1. Video 
  2. Audio
  3. Image files 
  4. Log files 
  5. Social media posts 

Semistructured data

Semistructured data is the combination of both structured and unstructured data. It does not follow any data model but still has some structure. 

Example:

  1. XML File 
  2. Emails 
  3. Zipped files 
  4. TCP/IP packets 

Also see, Must Do Coding Questions

Get the tech career you deserve, faster!
Connect with our expert counsellors to understand how to hack your way to success
User rating 4.7/5
1:1 doubt support
95% placement record
Akash Pal
Senior Software Engineer
326% Hike After Job Bootcamp
Himanshu Gusain
Programmer Analyst
32 LPA After Job Bootcamp
After Job
Bootcamp

Characteristics of Data

Let's consider each of these characteristics:

  • Type: Type represents the category of data. Data can be qualitative or quantitative. Qualitative data is non-numerical data like textual, opinions, observations, feelings, etc. Quantitative data includes measurements, counts, and other numerical aspects.

 

  • Level of Measurement: Data, after being categorized, is further classified based on its level of measurement. It depends on the precision and accuracy of the data. The measures can be interval, ordinal, nominal, or ratio depending upon the category and the precision of the data.

 

  • Distribution: Data can be normally distributed(the distribution is uniform, and the shape is symmetrical along the y-axis) and skewed (the data distribution is not uniform, and the shape is distorted and asymmetrical).

 

  • Size: Data quantity represents the size. In the case of big data, different techniques and tools are used for processing.

 

  • Central Tendency: The measurement of central tendencies of data is essential when dealing with quantitative data. The calculations and accuracy depend upon the data's mean, median, and mode.

 

  • Variability: The dispersion of data is its variability. The range, variance, and standard deviation are the factors of the variability of data. Here the data is quantitative.

 

  • Missing Values: These represent the incompleteness of data. Certain values are missing or are NULL values. In many cases, we replace the missing values with the mean value of the data.

 

  • Outliers: Outliers are extreme data values that differ from the other values of the data set. 

Recommended Topic, YII Framework and Mercurial

What is Information?

Information is processed data with meaning. Information is the collection of valid, meaningful, and understandable data. It represents an organized form of data or knowledge that can be stored and communicated in different ways, like images, audio, and video. It is easier to understand, learn and use.

What is Information?

This information has many different properties. Let's discuss these properties and characteristics in detail.

Also See, Ibegin TCS

Characteristics of Information

These characteristics differentiate data from information.

  • Relevance: The information should be relevant according to the task or subject. It should have meaning depending on the situation or topic.

 

  • Accuracy: The information should be accurate. It must be free from errors and plagiarism, and redundancy.

 

  • Timeliness: The information must be updated and refreshed frequently. 

 

  • Completeness: Completeness is necessary. The information should be detailed and cover all the relevant points. Half-knowledge is always dangerous. 

 

  • Objectivity: Information should be generalized. It should not be based on personal opinions or judgments. It should be unbiased.

 

  • Accessibility: Information should be accessible to everyone. 

 

  • Clarity: Information should be in a simple and understandable format. Readability should be checked based on the target audience. 

 

  • Credibility: Information should have evidence of its correctness.
     

Click on the following link to read further : Hackerearth Test Questions and Answers

Comparison Table Between Data and Information

Basis Data Information
Meaning  Data is the combination of raw facts and figures that are structured and unstructured and does not follow a particular format.

Information is the processed data that has meaning. It is a collection of data that has been trained and polished in such a way that it is valid, meaningful, and understandable.

 

Types  Quantitative and Qualitative data 

Processed and structured quantitative and qualitative data

 

Based on

Sources, Records, and Observations

 

Analysis and Measurements 
Useful  It may or may not be helpful  Useful 
Storage Format  No particular format  Stored in a specific format (.csv,.mp3)
Dependency  No dependency on information Without data, the information cannot be obtained 
Accuracy  Less accurate  Highly accurate 
Missing values  Contains Null and missing values  It does not have any missing value.


You can also read about mock interview.

The Key Differences Between Data vs Information

Data and information are related but distinct concepts:

Nature:

  • Data: Raw facts, figures, or symbols.
  • Information: Processed, organized, and meaningful data.

Meaning:

  • Data: Often lacks context or relevance.
  • Information: Has context and relevance, providing knowledge.

Usefulness:

  • Data: Requires interpretation to be useful.
  • Information: Immediately useful for decision-making.

Structure:

  • Data: Unstructured or semi-structured.
  • Information: Organized and structured.

Volume:

  • Data: Can be vast, including redundant or irrelevant items.
  • Information: Usually concise and pertinent.

Temporal Aspect:

  • Data: Can be historical or real-time.
  • Information: Typically reflects the current state or a specific timeframe.

Interpretation:

  • Data: Open to various interpretations.
  • Information: Presents a specific interpretation.

Communication:

  • Data: Can be transmitted without context.
  • Information: Requires context for meaningful communication.

Purpose:

  • Data: Often serves as the foundation for creating information.
  • Information: Used for decision-making and knowledge dissemination.

Transformation:

  • Data: Is transformed into information through processing and analysis.
  • Information: Is further processed into knowledge.

In summary, data is the raw material that, when processed and organized, becomes information. Information, in turn, is what we use to make informed decisions and gain insights.

Example of Data and Information

  • Example:
    Data: "1001010" (binary code) 
    Information: "1001010" translates to "74" in decimal, which represents the ASCII character "J." The context and meaning turn data into information.
     
  • Example:
    Data: "10°C" 
    Information: "The current temperature is 10 degrees Celsius." The data is transformed into information with context, making it meaningful and useful.

Frequently Asked Questions 

What are 3 differences between data and information?

  1. Data consists of raw facts or figures, while information is data processed into a meaningful context.
  2. Data lacks immediate usefulness, whereas information aids in decision-making.
  3. Data requires interpretation; information is interpreted and structured.

What are the 5 examples of information?

  1. Weather Forecast: Predicted conditions, temperatures, and precipitation.
  2. Financial Report: Income, expenses, and investment data.
  3. News Article: Current events and stories.
  4. Medical Diagnosis: Health assessment and treatment recommendations.
  5. GPS Directions: Navigational instructions and maps.

Which are the 3 main types of data?

  1. Structured Data: Organized and easily searchable, often found in databases.
  2. Semi-Structured Data: Contains structure but not as rigid as structured data (e.g., XML, JSON).
  3. Unstructured Data: Lacks a predefined structure, including text, images, audio, and video.

Conclusion 

This article contains content related to Data and information. In this article, the difference between data and information is mentioned. 

To learn more about the characteristics of data and information, you can visit the code studio by Coding Ninjas. Refer to our guided paths on Coding Ninjas Studio to learn more about DSA, Competitive Programming, JavaScript, System Design, etc. Enroll in our courses and refer to the mock test and problems available; take a look at the interview experiences and interview bundle for placement preparations.

Previous article
What is Coaxial Cable?
Next article
Data Transformation
Live masterclass