Types of Data

Dr Nic’s Maths and Stats

Data is defined as a collection of a particular quantity. Different quantities are represented as a set. The primary data and secondary data are a source of data.

Singularity for data is called ‘datum’. Collection of data can be done in two ways:

  • Census: a collection of data for every member of a group.
  • Sample: a collection of data of selected members of a group.

Data are of two types:-

  • Qualitative Data: They represent attributes. They depict a description that is observed which cannot be calculated.
  • Quantitative Data: they are measured and cannot be observed. They can be calculated and be numerically represented.

Types of Data Abstraction

Data Abstraction consists of complex data-structures. For easy retrieval of data & reduced compatibility, we use abstraction.

3 types of Abstraction:

  • Physical: this a low-level data abstraction. It tells how the data is stored.
  • Logical: this level stores information of data in the forms of the table.
  • View: Highest-level data abstraction. Users can view the database in the forms of rows and columns.

Types of Data Structure

Data structures are a way to store, organize, and function data in a particular order.

2 types of data structure:

  • Primitive Data Structures: They are performed at the machine level, can be used to make non-primitive data structures. They are predefined and are specific.

Examples: Integer, float, character, pointers

  • Non-Primitive Data Structures: These are derived data structures and cannot function without primitive data structures.

Examples: Arrays, Files, Lists

Types of Data in Statistics

  • Nominal Data: they are used to label variables without quantitative values.

Examples: Gender, hair color, nationalities

  • Ordinal Data: they are used to maintain the order of a database.

Example: depending on your happiness, how are you feeling,

  • Interval Data: it focuses on both order differences in variables of data. This allows measuring standard deviation and central tendency.

Example: Temperature in degree Celsius

  • Ratio Data: It specifies order, differences, and has zero value. It cannot have a negative value.

Example: Height

Types of Data Collection

Depending on the type of data, they are classified as:

  • Primary Data: Data that is collected for the first time for a specific purpose. These data are original and pure.

Example: Census of India

  • Secondary Data: Data that has been derived from the original content. It is impure as it has been statistically derived.

Example: Government of India Finance Report

Types of Data Model

Data modeling is a process that is used by an organization to rebuild, design, visualize through a graphical interface.

3 types of models:

  • Conceptual Data Models:  these are high-level, structures and concepts
  • Logical Data Models: provides a relationship between data entities
  • Physical Data Models: The internal layout database design
  1. Types of Data Models in DBMS
  • Hierarchical Model
  • Network Model
  • Entity-Relationship Model
  • Relational Model
  • Object-Oriented Data
  • Associative Data Model

Types of Data Analysis

The analysis is important to perform better and helps for decision-making.

4 types of data analysis vary from simple to complex methods.

  • Descriptive Analysis
  • Diagnostic Analysis
  • Predictive Analysis
  • Prescriptive Analysis

Types of Data WareHouse

Data Warehousing is processed to collect and manage data from various sources. It is used to analyze and connect data.

3 types of Data Warehouses:

  • Enterprise Data Warehouse: it is a centralized system that provides a support system throughout the process.
  • Operational: It is used to store data when the data warehouse is not in support of needs.
  • Data Mart: it is a small set of data warehouse.

Types of Data Mining

Data mining is the process for finding valid and potentially useful patterns in huge data sets. It is a multi-disciplinary skill that uses machine learning, statistics, Artificial Intelligence, and database technology.

Types on which it can be implemented:

  • Relational databases
  • Data warehouses
  • Advanced DB and information repositories
  • Object-oriented and object-relational databases
  • Transactional and Spatial databases
  • Heterogeneous and legacy databases
  • Multimedia and streaming database
  • Text databases
  • Text mining and Web mining

Types of Data Entry

It is a work to enter specific data into a computer or device. To change the format of the desired data, here is where data entry comes into play.


  • Image Data Entry
  • Spreadsheet Data Entry
  • E-commerce product data entry
  • Remote Data Entry
  • Textual Data Entry

Types of Data Research

This type of data u collect will reflect the way you would manage.

 There are 4 types:-

  • Observational Data: data is collected through observation of a behavior activity.
  • Experimental Data: data is collected through active intervention to measure when a variable is altered.
  • Simulation Data: generated by operating real-time operations
  • Derived Data: Creates new information by transformation by existing data.

Types of Data in Cluster Analysis

Cluster analysis is done by collecting data points in such a way to characterize data in a specific way.


  • Centroid Clustering
  • Density Clustering
  • Distribution Clustering
  • Connectivity Clustering

Types of Data in Computer

It represents the type of data that you want to use for computer processing. Different programming languages require different data types.


  • Character
  • Data
  • String
  • Number

Types of Data Classification

It a process of organizing data in a relevant manner so that is protected against any threat.


  • Content-Based Classification: includes reviewing files and documents
  • Context-Based Classification: classifies files on metadata
  • User-Based Classification: classifies files based on manual knowledge.

Types of Data Analytics

It is a process of analyzing raw data to provide suitable information.

There are 4 different types of data analytics. The types vary from simpler to sophisticated process.

  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics

Types of Data Transmission

It is a process of transferring data from one device to another. Data transmitted can be in analog or digital form.


  • Serial Transmission: Transmission is done bit-after-bit in an organized specific order. It can be furthered classified into:
  1. Synchronous
  2. Asynchronous
  • Parallel Transmission: Can transmit multiple numbers of data, multiple times.

Types of Data Visualisation

It is defined as data that can be elaborated through visuals like bar charts or graphs making it user-friendly.


  • Temporal
  • Hierarchical
  • Network
  • Multidimensional
  • Geospatial

Types of Data Flow Diagrams

It is a graphical presentation of data that makes it more informative and easier to understand. 


  • Logical: describes certain functionality of a given process
  • Physical: describes the implementation of a logical data flow diagram


✅ What do you mean by data?

Data is distinct pieces of information, usually formatted in a special way. … Since the mid-1900s, people have used the word data to mean computer information that is transmitted or stored. Strictly speaking, data is the plural of datum, a single piece of information

✅ What is a Data example?

Data is defined as facts or figures, or information that’s stored in or used by a computer. An example of data is information collected for a research paper. An example of data is an email

✅ What is Data short for?

Data is a plural of datum, which is originally a Latin noun meaning “something given.” Today, data is used in English both as a plural noun meaning “facts or pieces of information”

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About the Author

Piyush values education and has studied from the top institutes of IIT Roorkee, IIM Bangalore, KTH Sweden and Tsinghua University in China. Post completing his MBA, he has worked with the world’s # 1 consulting firm, The Boston Consulting Group and focused on building sales and marketing verticals for top MNCs and Indian business houses.

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