Data Classification

What is Data Classification?

Data classification is the process of organising data according to relevant categories for efficient usage. It helps to locate and retrieve data quickly. This process is vital when it comes to security, compliance, and risk management.

Classification of data meaning, tagging data so that it can be easily tracked. Moreover, it eliminates duplicate data which frees up storage space, lowers backup cost, and accelerates the search process. 

Types of Data Classification

There are three types

  1. Content-based classification stands for categorising data based on the sensitivity of the information it contains.

  2. Context-based classification stands for segregating data based on its application, location, its creator, along with other factors like characteristics of the information and indirect indicators.

  3. User-based classification is an entirely manual process. It depends on the decision of users on how they want to tag each data. 

Data Classification Methods

Some of the most significant methods are –

  1. Manual interval

  2. Defined interval

  3. Equal Interval

  4. Geometrical interval

  5. Quantile

  6. Natural Breaks

  7. Maximum breaks

  8. Standard deviation

Objectives of Classification of Data

Its objectives are –

  1. Simplification: It helps to present data concisely. Hence, it becomes more convenient to analyse data.

  2. Improves Utility: Classification brings out the similarity in different sets of data, which enhances its utility.

  3. Brings out Individuality: Classification of data in statistics helps in grouping them in various subheads. This process brings out the uniqueness of each data and assists in its better study. 

  4. Aids Comparison: It facilitates easy comparison with a substantial volume of data.

  5. Increase Reliability: Classification is a scientific process, and its effectiveness is proven. Therefore, this process increases the reliability of a specific set of data.

  6. Make it Attractive: One of the main objectives of data classification is to make it more attractive and enhance its presentation value.

Characteristics of an Impressive Classification

  • The primary feature of proper classification is that it makes the data comprehensive. It will cover every item in a set and segregate them in appropriate groups.

  • Every data set lacks clarity owing to its volume. This classification brings much-needed clarity and makes it easier to navigate.

  • Data in a set is often scattered in various places. Classification brings similar information under a single group and improves the homogeneity.

  • Every impressive classification must have elasticity, so that, if the purpose of classification changes the basis of it can change easily.

Data classification is a vital part of economics. Therefore, students who want to learn more about it in detail can visit the official website of Vedantu.

FAQ (Frequently Asked Questions)

1. What is the Meaning of Data Classification?

Ans: The meaning of data classification is to arrange data according to their common characteristics into similar groups. Raw data lacks clarity, and it is hard to navigate through it. This classification process eliminates these hurdles and makes it easier to analyse.

2. What are the Types of Data Classification?

Ans: There are three major types of data classification; these are content-wise, context-wise and user-based.