Computer Fundamentals - Data and Information

What is Data?

Data is a raw material; it’s a collection of facts and figures. Data does not have a significant meaning because of its raw nature. Data may include text, figures, facts, images, numbers, graphs, and symbols and it can be generated from different sources like sensors, surveys, transactions, social media etc.

G15, KPL, and Gud are some examples of data. Data needs to be processed to convert into a useful manner which is known as information. For example – Gud is data; after text processing, it converts into Good which is information.

Data
  • Raw material
  • Unstructured information
  • It has no context
  • Processed Data
  • Structured information
  • It has context

A proper analysis of data plays an important role in fields like research, science, business, healthcare, agriculture, and technology, driving decision-making and innovation.

Characteristics of Data

Some characteristics of different types of data are as follows −

Type of Data Characteristics
Quantitative Data
  • It's in numerical nature.
  • It can be measured and quantified like height, weight, temperature, etc.
  • This type of data can be analysed using statistical methods.
Qualitative / Descriptive Data
  • It is descriptive.
  • It can be explored using colours, textures, opinions or any other related feature.
  • It's often subjective which requires interpretation.
  • It can be categorical or ordinal.
Structured Data
  • It is organized in a predefined structure and usually includes a tabular form like databases, or spreadsheets.
  • Easy to search
  • It can be analysed using standard tools like SQL.
  • Allows performing queries to insert, delete and update.
Unstructured Data
  • It lacks a predefined structure.
  • It does not have a pre-defined structure.
  • It may include text documents, social media posts, images, videos, etc.
  • It is difficult to analyse using traditional methods.
  • It processes using advanced techniques like natural language processing (NLP), machine learning, etc.
Big Data
  • Data are bigger.
  • It is complex and processes using traditional data processing applications.
  • It has five V's to identify i.e. volume, velocity, variety, veracity, and value.
Metadata
  • It gives information on data about data.
  • It includes data dictionaries, file descriptions, tags, etc.
  • It gives a direction to understand, manage, and improve data search ability and usability.
Streaming Data
  • It is continuously generated and transmitted in a real-time environment like sensor data, social media updates, financial market data, etc.
  • It requires real-time data processing.
  • It often uses applications like IoT, real-time analytics, etc.

Types of Data

Types of Data
Quantitative data It's available in numerical form, like 50 Kg, 165 cm, 15887 etc.
Discrete Data Data that take certain values like whole numbers. For example, the number of employees in a department.
Continuous Data Data that can take any value within a range. For example, wind speed, and temperature. For example - Over time, certain continuous data, such as the weight of the baby over the year changes or the temperature in the room during the day changes.
Qualitative data It's available in a descriptive form for example name, gender, address, and features of a person.
Nominal Data Data that represents categories with no inherent order. For example, colours, and gender.
Ordinal Data Data that represents categories with a specific order or ranking. For example, ranking satisfaction levels as "poor," "average," or "excellent."
Categorical Data The data which represents categories or labels and is often qualitative is called categorical data. It can include nominal and ordinal data.
Numerical Data This type of data includes numbers. It can be either quantitative or qualitative.
Time Series Data Data collected over time intervals like stock prices, weather data, and sales figures.
Spatial Data Data associated with geographic locations like Google maps, GPS data, and satellite images.

What is Information?

Information is processed data. It is always useful and used in decision-making. A person who has a lot of information about a particular thing is always considered a knowledgeable person. Hence, a good information base always makes a good knowledge base and a good knowledge base helps to make healthy or fruitful decisions.

Characteristics of Information

General Characteristics of Information are as follows −

  • It is effective and complete to make decisions.
  • True information is broad in scope.
  • Information relates to the current situation and has an acceptable level of integrity.
  • Information is always compatible with response time.
  • Information is concise and does not contain delicacy.
  • Information is precise and accurate.
  • Information is always relevant.
  • Information can be verifiable.
  • Information contains facts; that can be shared for making fruitful decisions.
  • Information is organised and stored for future reference.

Differences Between Data vs Information

S.No Data Information
1 Data is a raw material It's processed data
2 It is meaningless It is meaningful
3 Is not use in decision-making Uses in decision-making
4 Data does not rely on information The information relies on data
5 Data is a collection of facts Information kept facts in context
6 Data is unorganized Information is organized
7 Data is represented in the form of graphs, numbers, figures, or statistics Information is presented in the form of words, language, thoughts, and ideas.
8 Data does not have context Information has context
9 It can be considered as a single unit that is unprocessed It is a product and a collection of data
10 It is measured in bytes and bits. It is measured using meaningful units like concerning quantity and time
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